hypothesis in developmental psychology

2.4 Developing a Hypothesis

Learning objectives.

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Before describing how to develop a hypothesis it is imporant to distinguish betwee a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition. He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.

Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.

A hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observation before we can develop a broader theory.

Theories and hypotheses always have this if-then relationship. “ If drive theory is correct, then cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.

But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this question is an interesting one on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [1] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). A researcher begins with a set of phenomena and either constructs a theory to explain or interpret them or chooses an existing theory to work with. He or she then makes a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researcher then conducts an empirical study to test the hypothesis. Finally, he or she reevaluates the theory in light of the new results and revises it if necessary. This process is usually conceptualized as a cycle because the researcher can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 2.2 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

Figure 4.4 Hypothetico-Deductive Method Combined With the General Model of Scientific Research in Psychology Together they form a model of theoretically motivated research.

Figure 2.2 Hypothetico-Deductive Method Combined With the General Model of Scientific Research in Psychology Together they form a model of theoretically motivated research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [2] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans (Zajonc & Sales, 1966) [3] in many other studies afterward).

Incorporating Theory into Your Research

When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.

Characteristics of a Good Hypothesis

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that really it does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

Key Takeaways

A theory is broad in nature and explains larger bodies of data. A hypothesis is more specific and makes a prediction about the outcome of a particular study.
Working with theories is not “icing on the cake.” It is a basic ingredient of psychological research.
Like other scientists, psychologists use the hypothetico-deductive method. They construct theories to explain or interpret phenomena (or work with existing theories), derive hypotheses from their theories, test the hypotheses, and then reevaluate the theories in light of the new results.
Practice: Find a recent empirical research report in a professional journal. Read the introduction and highlight in different colors descriptions of theories and hypotheses.
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

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Developing a Hypothesis

Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton

Learning Objectives

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Before describing how to develop a hypothesis, it is important to distinguish between a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition (1965) [1] . He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers begin with a set of phenomena and either construct a theory to explain or interpret them or choose an existing theory to work with. They then make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary. This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 2.3 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [3] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans [Zajonc & Sales, 1966] [4] in many other studies afterward).

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that it really does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

Zajonc, R. B. (1965). Social facilitation. Science, 149 , 269–274 ↵
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

A coherent explanation or interpretation of one or more phenomena.

A specific prediction about a new phenomenon that should be observed if a particular theory is accurate.

A cyclical process of theory development, starting with an observed phenomenon, then developing or using a theory to make a specific prediction of what should happen if that theory is correct, testing that prediction, refining the theory in light of the findings, and using that refined theory to develop new hypotheses, and so on.

The ability to test the hypothesis using the methods of science and the possibility to gather evidence that will disconfirm the hypothesis if it is indeed false.

Developing a Hypothesis Copyright © 2022 by Rajiv S. Jhangiani; I-Chant A. Chiang; Carrie Cuttler; and Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Methodology

How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

An independent variable is something the researcher changes or controls.
A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

The relevant variables
The specific group being studied
The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Sampling methods
Simple random sampling
Stratified sampling
Cluster sampling
Likert scales
Reproducibility

Statistics

Null hypothesis
Statistical power
Probability distribution
Effect size
Poisson distribution

Research bias

Optimism bias
Cognitive bias
Implicit bias
Hawthorne effect
Anchoring bias
Explicit bias

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Lifespan Development: A Psychological Perspective - Fourth Edition

(38 reviews)

Martha Lally, College of Lake County

Suzanne Valentine-French, College of Lake County

Last Update: 2023

Publisher: Martha Lally, Suzanne Valentine-French

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Michael Shaughnessy, Professor, Eastern New Mexico University on 1/16/24

Comprehensiveness rating: 5 see less

This is a VERY comprehensive book, integrating historical, medical and psychological information as it relates to human growth and development. That being said at 496 pages- it is really a graduate level book- as undergraduates would be overwhelmed with it and its comprehensiveness. It is up to date and chock full of tables and figures and pictures and is well organized and rich and robust with depth.

Content Accuracy rating: 5

From what I have seen the book is accurate, and while I did not read every word of every page of this 496 page book- what I have read seems on target and relevant and unbiased.

Relevance/Longevity rating: 5

Very timely and relevant- one notices the mention of COVID and it's impact on learning and the growth and development of the human organism. Artificial intelligence will be integrated into this 10 chapter book relatively quickly. At first, when I saw 10 chapters, I thought this would be a superficial summary type of book but it is surprisingly an indepth very comprehensive book- one that might fit into an honors class.

Clarity rating: 5

Clarity is good- but this book would need to be a text for a 16-week course- to allow students to read and reflect and absorb the material.

Consistency rating: 5

Logical rational and reasonable---but the length is overwhelming- students might intially be drawn to the pictures charts and graphs- but this is a graduate level text for a graduate level class- in which the graduate students have plenty of time to read and review and reflect.

Modularity rating: 4

This is a ten-chapter book- but it really delves into each chapter extensively. I was initially happy to see the 10-chapter organization- but each of these chapters is rich and robust and in depth-. I suppose that students could be told to skim over the historical and medical parts and just glance at the charts and graphs and figures- but this is a THICK book- 496 pages- and it deserves a full semester. I would NOT recommend this for a summer class.

Organization/Structure/Flow rating: 5

It is easy to reflect on the organization as it covers the human development from birth to death - and does so comprehensively. This is a book for reflective scholars- who want to stop and think about and in class- to discuss all of the issues comprehensively covered.

Interface rating: 5

Charts, graphs, figures---are all clean and neat---font could be larger in SOME places- but BOLD is used for terms and headings- and this is nicely organized.

Grammatical Errors rating: 5

Readable, enjoyable, conversational----but time has to be allocated for a real reading of this 496 page tome.

Cultural Relevance rating: 5

The authors seem to have worked on this- and I have seen a balance here- and I have no concerns or objections.

As I have already mentioned,----this is a book that deserves a full semester---and should not be used in a 4-week summer class or any 8-week approach. This book deserves the time to absorb, think about and reflect on the material that is interwoven with theory and factual knowledge and information. This is a rich robust, but thick challenging book for serious graduate students who really do want to learn more not just about human growth and development- but the human condition !

Reviewed by Kelli Rogers, Assistant Professor Practice, University of Texas at Arlington on 12/12/22

Comprehensiveness rating: 4 see less

This text examines how biological, psychological, and social factors shape people’s lives from conception to death, covering various stages of development and a number of theories relates to these stages. However, there is need for further discussion of atypical development and the influence of various social, cultural, and environmental contexts. There is no glossary, which would be helpful for students who prefer to print the text.

Content Accuracy rating: 4

The content parallels other text on lifespan development and course curricula. However, more contemporary research would increased its accuracy. Detailed discussions of risk and protective factors relative to each of the stages of development would provide a more comprehensive perspective. In addition, other issues of diversity (besides just socioeconomic background and culture) should be described.

Relevance/Longevity rating: 4

This text contains relevant information, however, there are several older references. While this may be appropriate for theoretical and historical discussions of human development, it fails to include updates in science and technology that significantly influences development. In addition, the inclusion of case vignettes would improve relevance and engagement. The text is written and arranged in such a way that necessary updates will be relatively easy and straightforward to implement.

This text is well-organized and easy to read, which makes it ideal for undergraduates. The learning objectives could be more concisely written, as there are several sets of topic-specific learning objectives in each chapter.

Consistency rating: 4

The text appears to be presented in a consistent manner, with regard to terminology and framework. However, the degree of depth to which theories and concepts are covered varies. For example, there are fewer theories discussed in chapters middle adulthood through late adulthood, which may be a reflection of current literature.

Modularity rating: 5

The text consists of 10 chapters, organized by developmental stages and can be easily reorganized and realigned for a variety of course modalities. The text is also easily and readily divisible into smaller reading sections that can be assigned at different points within the course

Organization/Structure/Flow rating: 4

The topics in the text are presented in a logical, clear fashion and the layout remain consistent across all chapters. However, some chapter lack a smooth transition between subsections and topics.

The text is free of significant interface issues. The table of contents and external links embedded within the chapters are navigable. The charts and images are readable.

I did not noticed any grammatical errors or issues.

Cultural Relevance rating: 4

I would have appreciated more content on issues of diversity and how this significantly impacts various stages of development. Ageism was limited to experiences in late adulthood ad fails to discuss ageism in adolescence. Case study examples of a variety of backgrounds, disabilities and abilities, religions/spirituality, etc., would improve cultural sensitivity and inclusivity. More diverse images and the inclusion of studies of nonwhite populations would be beneficial.

Overall, I found this text to be very comprehensive in covering all of the developmental stages and major theories of development. While the majority of the content is consistent with other texts, supplemental reading materials, documentaries, case vignettes, etc., are necessary to improve relevance, accuracy, and inclusiveness.

Reviewed by Michael Slavkin, Assistant Professor of Psychological Services and Counseling, Marian University on 5/31/22

Each chapter is organized around a developmental level. Pertinent theories and concepts are covered. Details are strong and material is well discussed. read more

Each chapter is organized around a developmental level. Pertinent theories and concepts are covered. Details are strong and material is well discussed.

No accuracy issues were evidenced. The text is error-free and no bias seems to exist. Relevant information and up-to date references.

The textbook is relevant, providing current information that links with the current research in the field. There is a clear arrangement as the text is tied to areas of development. The fact that there are 10 chapters makes the text fairly straightforward to implement over the course of a term.

No clarity issues were found. The text is written in a clear style, and provides good content with limited jargon. Those terms that are new are highlighted for student ease (no glossary is included, but bolded words are used for new terms).

The text is internally consistent, using a clear organizational scheme. There is no issue with framework, and material could be supplemented easily.

The text is divided into 10 chapters, which could be aligned to different course management systems easily. The text is not overly self-referential. It can be organized and aligned with articles or materials relatively easily.

The topics in the text are organized well. The material is clearly stated, and presented relatively easily for review.

No navigation problems or distorted in any way. The text was displayed well.

Clear text with no grammatical issues.

The book does an exemplary job of sharing up-to-date material that supports a strong multicultural and diverse background. Details about exceptionalities, neurodiversity, and cultural/social sensitivity are included.

The text by Martha Lally and Suzanne Valentine-French is a solid overview of lifespan development. Appropriate for psychology, sociology, education, and human services; this would be a strong textbook for use in a variety of programs. Well organized and developed.

Reviewed by Joshua Smith, Psychology Instructor, Dodge City Community College on 2/25/22

This book is well laid out and covers all of the major areas of the lifespan development. The book is hits on all of the major concepts and theories that I would want to teach in an introductory or intermediate lifespan development course. The book does not contain a list of key terms and definitions at the end of the chapters or a glossary. An index at the end of the text would also be helpful.

Content in the text is consistent with other introductory development textbooks. Historical and theoretical information is accurate and contemporary examples are beneficial. The text presents information that is consistent with psychological theory and supported by research in a way that appears free of any overt bias.

The text was updated in 2019, but still contains several older references. Depending on your teaching goals (e.g., theoretical foundations vs. modern applications), the addition of more recent works could be beneficial. Instructors might need to supplement with recent research in some areas. There have been some updates from previous versions, such as the inclusion of social media and its influences on adolescents.

Clarity rating: 4

The text is clear and should be relatively easy for the average undergraduate student to understand. Major terms and concepts are generally defined in context as you read each chapter, but definitional content could be better. A glossary would help with this. It may occasionally be challenging for students to differentiate major theories or concepts from examples and elaborations on those concepts.

The table of contents is very informative and aligns clearly with the layout of each chapter. Chapter layouts are consistent and easy to follow, making the text very easy to navigate. An index at the end of the text would be helpful for students looking for concepts that are not major chapter or sections headings.

The organization and presentation of chapters follows the unfolding of the human lifespan, so reordering the text is not likely to be necessary. Within each chapter, the text is easily divisible into smaller sections for reading or teaching.

Chapters are clear and logically organized. Presentation of chapter topics follows the unfolding of the human lifespan which is appropriate for a lifespan course. Some instructors might choose to reorder subtopics and sections within a chapter which could easily be done.

Interface rating: 4

The interface is smooth. You can click on chapter titles or subsections from the expanded table of contents to be linked directly to that section of the text. However, navigation within each chapter would be more smooth if the bookmark function was used in the left navigation bar to provide point and click navigation to each chapter and section as you read.

I did not notice any grammatical errors during my review.

There is a nice, if small, section on culture and development in chapter one, but this is not detailed. In several areas, the text touches on culture and diversity, and explores their impact on development. For example, the text brings up cultural influences on cognitive development and education, gender and gender identity, parenting behaviors, marriage practices, and many other areas. However, as with many introductory texts the predominant focus is on white-western culture which serves as the normative comparison point for other groups.

I would use this text for my introductory course in developmental psychology.

Reviewed by Elbert Davis, Assistant Professor, Marshall University on 12/17/21

This is a very in-depth textbook on lifespan development. The authors follow the lifespan from pre-birth to death. The theories are introducted in the first chapter, and are again discussed in the relevant developmental stage in future chapters.... read more

The content of the textbook relies on factual information, providing references at the end of each chapter. Author bias was not observed. Errors were not evident.

This textbook would be easy to update. The chapters are broken into many different sections, which is reflected in the table of contents. While lifespan development is not a new concept, the authors included information on transgendered persons, which is not something usually discussed. That was refreshing to see.

The authors introduce jargon and new terminology by highlighting in purple. They also do a great job in breaking up text by using graphics and tables.

The chapters are arranged using the same basic framework, which makes it easier on the reader to know what to expect.

The authors use extensive subheadings to break up the material, as well as images and tables.

The topic of lifespan development makes it easier for organization. The authors started with pre-birth and discussed the various stages of development, inlcuding infancy, childhood, and adulthood, until death.

There was nothing confusing or distorted in the book. Navigation was easy. The subheadings in the table of contents were clickable, making it easy to navigate.

No graamatical errors were evident throughout the book.

Cultural diversity is woven into the chapters, as well as students with learning disabilites.

Reviewed by Lisamarie Bensman, Assistant Professor, Windward Community College on 12/12/21

This text includes all major areas of development that I would expect to find in a developmental text. The index at the beginning of the text is useful for a quick overview of what is in each chapter and can be used to jump to specific sections. There isn’t a glossary, which has its positives and negatives. Glossaries can be super helpful in reminding students of what terminology means, but they can also provide students with an oversimplified idea of those concepts, so for me a glossary is not a deal breaker.

The content in the text is accurate and provides a solid introduction to development. I was particularly pleased with how the authors presented Freud, as they appropriately acknowledged his lasting contributions to development, as well as the limitations of his work, and did so without his presenting his unsupported, unscientific theory of psychosexual development followed by the usual disclaimer. Avoiding this standard but very flawed way that many developmental texts handle Freud set a tone early on that the authors thought carefully about the validity of the content that they included and would present only the most accurate, scientifically supported information. That trend appears to have continued throughout the text (with a few exceptions, please see comments on relevance).

The majority of the content appears to be as current as can reasonably be expected for any text and, in some places, even more current than would be expected (for instance, when I selected this text in 2019 it already included a small section on children in detention centers at the southern US border and the impact separation and stress has on children, as well as the APA’s opposition to family separations). There are a few places, particularly in regards to pregnant individuals in the second chapter and in regards to gender identity that language could be more inclusive and better reflect current research and understanding, but even then, the language and understandings used are not that out of date nor different from how many developmental texts approach these issues (I’m not saying this standard approach is a good thing, merely a common issue).

The writing in this text is clear and easy to follow. The style is a bit more formal than would be my ideal for my particular students, but it’s not overly formal in an off-putting way. The syntax is appropriate for college students of all levels.

The text is consistent in the framework and terminology used. As a developmental text, it follows a standard organizational format for each chapter (after the beginning two foundational chapters and minus the final chapter on death and dying). The authors clearly, consistently, and appropriately reference back to the same theories and concepts throughout each chapter (adding new developmental concepts and removing old concepts, as appropriate). They provide enough context each time that a past theory/concept is presented to remind students what the students already know without giving so much context that students feel like they are re-reading the same information over and over again.

The chapters in the text are a bit lengthy because they cover all areas of development within the chapter’s developmental time period. If desired, smaller sections within each chapter could be assigned using page numbers. But there’s only one link for the whole book, as opposed to separate links per chapter or section, so if you were going to assign sections within each chapter separately, you’d have to first figure out the page numbers and then students would have to navigate to those sections. This isn’t the end of the world, just like navigating to each chapter isn’t the end of the world, but it might be something you or your students find annoying. As this is a developmental textbook, I wouldn’t suggest doing the chapters or sections out of order (I’d say the same for any developmental text).

This text is well organized. It has one chapter per developmental time period with each chapter progressing from physical development to cognitive development and ending with social development. Putting all three areas of development into one chapter does make the chapters long, but students seem to think they have less reading this way than with development textbooks that do three chapters per developmental time period (i.e. one chapter per area). Within each chapter, the topic order makes sense and follows naturally.

Interface rating: 3

The interface for this book is okay. The text and images flow well together. There are no confusing breaks/blank spaces or distorted images. That being said, it’s not the easiest text to navigate. If you know what page you want or remember to use the table of contents at the beginning of the text (which does allow you to jump directly to a section), you’re all set. But if you’re in a chapter and want something else in that chapter, it’s a scroll till you find it or use ctrl-F a lot type situation. On the left-hand side of the .pdf are thumbnails of the pages, but a linked table of contents would be easier. That way, the sections and order of the chapter could be seen at a glance and, if linked, one could jump directly to the desired section.

There are no large grammatical errors of note. For the most part, the text reads well/easily. There are a few hiccups here and there, but nothing overwhelming, nor do the small issues happen enough to be off-putting or undermine confidence in content.

Cultural Relevance rating: 3

Based on the reviews, I expected more discussion of culture than I found in this text. Even the ‘issues in development’ section in chapter 1 is missing the question of whether development is universal or particularistic, an overarching question addressed in most developmental classes. That being said, there are some sections throughout the text that do mention the impact of culture. In a related vein, as far as diversity goes, while there is some diversity mentioned, there isn’t as much diversity as needed to reflect real life. Even the images selected skew highly Caucasian in many sections. This lack of diversity made the text less relevant to my students who are extremely diverse and might struggle to see themselves in the images and descriptions given.

Generally, I am satisfied with this text. I am currently finishing my fourth semester teaching with it. Students have reported that they find the book easy to read and engaging enough. I typically describe it as a solid text without the bells and whistles of the new for-purchase textbooks and that my students as a group get more out of this text that they can afford to read than they would out of a flashy, interactive text that few of them can afford to buy. I do recommend this text to other instructors.

Reviewed by Mary Ann Woodman, Adjunct Professor, Rogue Community College on 12/8/21

The content material in this book is very easy to read and well organized. It provides a comprehensive look at the stages of human growth over time including theoretical, methodological and historical approaches to lifespan development. Chapter 1: Introduction to Lifespan Development Chapter 2: Heredity, Prenatal Development, and Birth Chapter 3: Infancy and Toddlerhood Chapter 4: Early Childhood Chapter 5: Middle and Late Childhood Chapter 6: Adolescence Chapter 7: Emerging and Early Adulthood Chapter 8: Middle Adulthood Chapter 9: Late Adulthood Chapter 10: Death and Dying Each chapter presents physical development, cognitive development, and psychosocial (or social and emotional) development.

The information is historically accurate, unbiased and without error. It includes a balance of history and contemporary theories and concerns. The information in this text appears accurate, error-free, and unbiased. There is a great deal of content in each chapter from birth to death and all stages in between. Within each category of development, physical, cognitive, and psychosocial development is covered along with stories and examples to support the theories. It also contains links to other resources for students to consider as they study.

The book was completed in 2019, so it is up to date, written and arranged in a way that provides for updates in an easy and straightforward manner. An instructor can easily supplement the material with current issues relevant to the material presented in each stage of human development. The bibliography at the end is also helpful.

The authors writing style is lucid, easily accessible with college level terminology. The learning objectives make it easy for student outcomes and instructor assessment. It would be beneficial to include a glossary and make certain the PDF meets standards of accessibility according to federal legislation.

Each chapter is laid out in a developmental structure with sub-headings that make it consistent in framework. There are no inconsistencies in terminology. The bold vocabulary and italic definitions are a desirable feature and the print size very readable.

The text is organized well and additional material could be added without presenting disruption to the reader. Because the content is already 468 pages, a bit much for college students to absorb in one term, it might be wise to condense some of the material if new content is later added.

Birth to death in a linear fashion is the mark of a book focused on Lifespan Development and this one offers physiology, psychology, sociology and research to support the content. It is well organized in chapters with clear subheadings, and very easy to follow.

The images, graphs, charts and visuals support and enhance the written material very well. Many students are visual learners therefore, this component adds a great deal for understanding the concepts. There are no places that distract or confuse the reader.

There are no grammatical errors in this book.

Most of the chapters include cultural sensitivity of race, ethnicity, and gender concerns. There is a fair amount of information focused on family diversity, religious populations, gender roles and inclusivity.

It will be a gift to offer this textbook at our College as the current cost of textbooks has risen to levels quite unaffordable by our students. Much appreciation to the authors for their incredible efforts in providing this resource for Lifespan Development Courses.

Reviewed by Jeongwoon Jeong, Instructor, Fort Hays State University on 10/20/21

The overall text covers comprehensive ideas including basic and advanced concepts of theories. It would have been better if the text included index or glossary. read more

The overall text covers comprehensive ideas including basic and advanced concepts of theories. It would have been better if the text included index or glossary.

The text content is mostly standard and accurate.

The text content is mostly up-to-date and relevant to each subject with different resources.

The text is well written and is to understand; however, it could have better if the text is more clearly separated between subjects and theories

The text is internally consistent in terms of terminology and framework. They also well included tables and images for each theory or framework

I can say that the text has a high readability by including smaller reading sections.

The topics in the text are well organized by theories and others but some sections are not clear whether they are listed headings or sub-headings.

The text included appropriate images but I would recommend to have more vibrant images.

The text contains no grammatical errors.

Since diversity is very important in our society, I hope that the text included more about cultural perspective in each chapter and theories.

Reviewed by Keonya Booker, Associate Professor, College of Charleston on 9/15/21

This textbook analyzes the human lifespan from birth until death. Each chapter includes a discussion about the physical, cognitive, and psychosocial changes that can be expected at every developmental stage. The expanded table of contents lists all sub-headed sections, but a clear distinction between the three aforementioned categories would have been useful. Terms are in bold print and defined for the reader. The addition of a glossary would be helpful for students who wish to have particular terms organized in one place.

Overall, the textbook is accurate. There are few errors that would significantly change the meaningful content of the book. As an introductory textbook, the major theories of development are presented correctly and without bias.

This textbook juxtaposes classic developmental theory (e.g., Sociocultural, Constructivism, Behaviorism) that will not change, with more recent information that may have to be updated. For example, in the late adulthood chapter the leading causes of death in the wake of COVID will likely have to be revisited. It should be easy to make these revisions. Since the last update was in 2019, another version could address this.

The writing was clear and without filler. Jargon is left to a minimum and examples are provided to help the reader understand complex terms. At times there is an overwhelming amount of statistical references, which can result in a sea of parenthetical percentages that may be hard for students to move through.

Each lifespan stage has a section devoted to physical, cognitive, and psychosocial development. The textbook is consistent with respect to its terminology and framework. A list of fully cited references are provided at the conclusion of each chapter.

In its current state, the textbook is in a PDF format. While the table of contents provides page numbers, it would be preferable to have a more reader-friendly searchable function such as hyperlinked headers, or another way to go to a specific part of the text. As it stands right now, the reader has to seek and scroll. Also, each chapter is very dense, some at more than 40 pages. In a typical twice or thrice weekly class schedule, an instructor may have to assign sections and specific pages at a time.

As this is a developmental psychology textbook, the authors presented the human lifespan in a logical fashion. The physiological and social implications of each developmental stage are addressed.

Most of the images added to the reading experience; however, a few were distorted and unclear. Replacing these images would be helpful. The figures and tables illuminated important topical ideas and research findings.

Grammatical Errors rating: 4

There were a handful of grammatical errors, some of which were within a bolded, defined term. Another thorough editing of the textbook could eliminate this issue.

The authors presented the qualities of the human experience from multiple cultural perspectives. Beyond racial and gender diversity, attention was paid to LGBTQ+ communities, neurodivergent populations, and those who are differently abled. Research was presented that explored how humans make sense of their worlds in a diverse set of circumstances and from a unique identity perspective. The inclusion of images that depicted various multicultural groups was an important component as well.

Thank you to the authors for providing an open source alternative to a traditionally published textbook. I appreciate the time and effort it took to complete such a large project.

Reviewed by Cebrail Karayigit, Assistant Professor, Pittsburg State University on 4/22/21

This book is comprehensive, and includes chapters on each stage of the lifespan. The book covers not only cognitive domain, but also biosocial and psychosocial development, involving continuity and change. The book also analyze different developmental events from the perspective of the major theories of development (e.g. Erikson, Kohlberg). This book also provides a thorough understanding of the timing and sequence of development throughout the lifespan.

The content of this is accurate and consistent with most developmental levels. However, there are few things in emerging adulthood section that I do not believe are fully up-to-date (e.g. emerging adulthood has been proposed as a new life stage between 18-29 in recent literature). Emerging adulthood and Early Adulthood could be covered separately and in different chapters.

The book explains how research contributes to the understanding of development. Although information included is mostly relevant to each developmental level, I do not see any focus on how use of social media plays a crucial role in adolescents' and emerging adults' lives.

The information presented is written very clearly, and the book is easy to follow.

The book has a consistent format and structure. The chapters has good internal consistency.

Each chapter could include a separate domain (e.g. cognitive, biosocial, and psychosocial/emotional), so it would make it easy to focus on specific topics across different developmental levels.

While the book has a consistent and logical structure, it would be helpful if the subsections in each chapter were arranged according to specific domain such as cognitive, biosocial, and psychosocial aspect.

Information is presented in a way that makes it easy to read and navigate. The book contains a lot of figures, graphs, and seems like a good fit with the online format.

No major grammatical errors were detected.

Although few chapters focus on diversity (e.g. chapter 1 and 8), it would make it more effective if each chapter included a section that attempt to analyze different developmental events from the perspective of non-Western perspective.

Reviewed by Dr. Charlene Moore-Peterson, Adjunct Professor, Aiken Technical College on 3/16/21

This book covers all areas effectively as it relates to the subject of Lifespan. read more

This book covers all areas effectively as it relates to the subject of Lifespan.

Accuracy is error and is unbiased.

Content in this book is updated and easy and straightforward to implement effectively.

This book provides adequate context.

Great consistency.

This book is easily readily divisible; broken down inyo section is quite helpful.

Well organized.

The text is free of interface issues.

Little to no grammatical errors.

The text is not culturally insensitive and is not offensive in anyway. Culturally appropriate.

Reviewed by Emily Healy, Assistant Professor, Bunker Hill Community College on 2/9/21

This textbook provides a comprehensive look at human growth and development over the lifespan. It begins with an introductory chapter, which looks at theoretical approaches to studying lifespan development, different methodological approaches to... read more

Chapter 1: Introduction to Lifespan Development Chapter 2: Heredity, Prenatal Development, and Birth Chapter 3: Infancy and Toddlerhood Chapter 4: Early Childhood Chapter 5: Middle and Late Childhood Chapter 6: Adolescence Chapter 7: Emerging and Early Adulthood Chapter 8: Middle Adulthood Chapter 9: Late Adulthood Chapter 10: Death and Dying

Each chapter and corresponding period of development is treated from different perspectives: physical development, cognitive development, and psychosocial (or social and emotional) development.

The information in this text is accurate, error-free, and unbiased. As a survey course, this book is tasked with covering a wide amount of information of the entire lifespan. The book looks at issues of heredity, prenatal development, birth, infancy and toddlerhood, early childhood, middle and late childhood, adolescence, emerging and early adulthood, middle adulthood, late adulthood, and death and dying. Within each category of development, physical, cognitive, and psychosocial (social-emotional) development is considered. Furthermore, each period of development includes special topics and categories that are more pertinent to those periods of development. For example, in the chapter on late adulthood, issues of retirement, neurocognitive disorders, elder abuse, and substance use disorders specifically in the elderly populations are treated. By contrast, in the chapter on adolescence, special topics include sexual development, eating disorders, and teenage drivers.

This book is likely to retain a high score in relevance in the coming decades. While it provides a wealth of information specific to each stage of lifespan development, the information is no so specific as though it will become obsolete or outdated quickly. This textbook provides a solid foundation upon which instructors and educators may build in relevant examples from current events. For example, in the chapter on middle and late childhood, while the topic of physical development is discussed and special topics of sports and childhood obesity are treated, an individual instructor can bring in information that is relevant and pertinent to the specific population in which he/she/they are teaching.

This text is written clearly, in an accessible manner, providing both context and working definitions for any technical terminology. The textbook introduces students to technical terminology used in the field of human growth and development in a scaffolded manner, where new concepts are introduced in appropriate context, are then defined. and the concepts are used in examples in order to improve reader comprehension. Each section of the chapter begins with the learning objectives for that particular section. The text utilizes headers and subheaders to clearly denote information organization. Vocabulary words are bolded and set in the text in purple, and definitions are in italics.

The textbook is organized in a consistent manner. Each chapter begins with an overview. Each section of the chapter contains a text box including learning objectives for that section. Each chapter (apart from the first introductory chapter) treats the subject matter from three broad domains or dimensions: 1. Physical development 2. Cognitive development 3. Psychosocial (social-emotional) development

Within the chapters, consistent formatting of headers and subheaders are used. It is a well-organized and highly navigable text overall, which is student-friendly.

On the whole, this text is easily divided into sections. Chapters do not run over into each other, as each chapter begins on a new page. The text also makes use of a consistent, predictable format, which makes it more predictable for the reader. The only drawback to the text that I have found with regard to its modularity is that it would be helpful if the three approaches (physical development, cognitive development, and psychosocial development) were also set apart. For my own classes, I treat physical and cognitive development on one day (or one week), and psychosocial development on another day (or week), and it is not readily divisible into these sections.

Overall, the organization of this text is clear and predictable. Each chapter is clearly listed, with topics clearly defined. Each section contains a set of learning objectives for that section. In addition, the chapters are organized in a repeating manner, then adding in topic-specific information for that particular stage of development.

The text is easily navigable, and is easily exported as a PDF (in the event that the instructor wishes to break the textbook down chapter-by-chapter for students, such as in an online learning environment where different topics are treated on a week-to-week basis).

The text is very culturally sensitive. Pictures in the text depict a wide array of diverse racial, ethnic, and religious populations (for example: BIPOC, Muslim individuals, etc.). Furthermore, discussions of special topics within chapters are treated from a multitude of perspectives. For example, in the section on religion, a wide variety of faith traditions are treated, rather than singling out one perspective. Furthermore, in the section on family units, different formulations of families (including step- and blended- families, as well as LBGT families) are included.

Reviewed by Jacqueline McMillion-Williams, Adjunct Professor, Bunker Hill Community College on 1/31/21, updated 2/1/21

For a course on developmental psychology, this text provides appropriate coverage of all areas of the lifespan. The table of contents provides an effective index in both short and long form. Key words are bold and defined within the text, but... read more

Accurate information about theory and application with diverse perspectives of the lifespan. Theory presented within a historical context with examples of life lived in a variety of circumstances that influence development.

There is a clear timeline of theory formation, historical context, and application to current society and with recent data. The arrangement of the text, with clear citations and reference information at the end of each chapter allows data to be easily located and updated. This is also true of the use of current slang; reflective of the time and society the text is written within, but also easy to locate and update.

From my perspective, the audience for this book is students and as such, a benefit of this book in comparison to those I have used in the past, is the use of common and approachable language. There is an appropriate use of jargon so the reader can place it in context. Although the text is clearly academic, it tells a clear story about development that engages the reader.

From the beginning, there is a clear framework of development for the reader to follow. Contents of each chapter and use of terminology stays consistent with the framework.

Authors divide the content of the textbook into sections that are logical for a comprehensive overview of the lifespan. Content is easy to divide into weekly readings or modules for student consumption and learning. Teachers could choose to assign in the original order or rearrange content by preference. Simultaneously the sections can be pulled out to be used a supplements for study in other courses on the lifespan such as early childhood, child psychology or adolescence and adult. You could also choose to restructure content to provide individual overviews of each theory.

Authors present topics in a logical sequence as chapters and subtopics are sections of each chapter. This makes the text easy to follow and annotate.

The textbook does not have any interface issues. It has appropriate headings to divide sections. Images and charts are clearly visible in color and black & white. Images are in appropriate locations that provide illustration of information. Alignment with text is complimentary.

I did not locate any grammatical errors in the text.

Text includes culturally relevant and sensitive examples of a variety of backgrounds (race, ethnicity, and sexual orientation) as well as about various aspects of biological, psychological and social influences on normalized development in a manner that may challenge students to rethink what is normal.

My use of this text with students is just beginning. Initial adoption occurred based on a recommendation from other faculty. Overall, the text is more up to date and culturally diverse than past texts I have used for similar and the same course. I would have liked some supplementary materials, but given the electronic format of the text, I have not found it difficult to create my own.

Reviewed by Meagan Docherty, Assistant Professor, Bowling Green State University on 12/15/20

This book is comprehensive, and includes chapters on each stage of the lifespan, as well as an introductory chapter with information on the lifespan perspective, theories, and research. Each chapter includes the major developmental changes and tasks associated with physical, cognitive, and socioemotional development. The table of contents is very detailed, and provides information on subheadings within each chapter.

This textbook is more accurate than others I've looked into using. It provides information on historical research and theory, while also providing a more contemporary perspective, and indicating when findings may be culture-dependent.

I think the content generally appears to be up to date, and includes more contemporary perspectives and recent research findings.

This book is written in a clear, simple style that I think would work well for undergraduate classes. New terms are introduced and explained clearly.

The book appears to be consistent in its approach and framework, including concepts covered and terms used.

With maybe a few exceptions, the text is generally broken up into several subheadings, making it easy to use certain sections on their own or reorganize material if needed.

I think overall the book is organized very well. Other lifespan psychology books tend to break chapters up into subsections for physical, cognitive, and social and emotional development, and it's my impression that undergraduate students appreciate that distinction, so it may help for a later edition of this book to adopt that organization.

Overall I think the book is laid out very well, but some of the charts and images appear to be low quality or dated. I like that there are links to sources embedded in chapters, but overall it does not have the same production quality that undergraduate students may be used to with current e-books.

I did not notice any grammatical errors in my reading of the book.

Overall I think the book does a good job of being inclusive and highlighting different cultural perspectives while being sensitive and appropriate.

I like the material covered in the book, and I think it would provide a good amount of breadth and depth for an undergraduate lifespan course. I think if the production quality was even higher, it would make the book even easier to adopt.

Reviewed by Amy Clinard, Assistant Professor, Bunker Hill Community College on 12/14/20, updated 12/18/20

The Table of Contents itemizes lifespan development just in terms of the stages of the lifespan (infancy, early childhood, etc.) and does not further itemize based on domains which many other textbooks do (physical, cognitive, psychosocial). Although the full table of contents does provide an exhaustive list of specific topics covered within each of those lifespan stages, it might have been better to have those topics itemized by domains.

I very much appreciated the level of accuracy and the unbiased nature of this textbook. It is clear that the authors were deliberate in integrating multiple diverse perspectives into their work. I have not found any major content errors.

This textbook is notably up-to-date and contains many timely, current and important conversations that are not always found in textbooks. It would seem that any necessary updates will be easily implemented as a result.

This textbook is written in a way that is clear, accessibly, and ELL friendly. It clearly identifies, defines and explains psychological jargon and technical terms in a way that is easily understood by the reader.

The text is exceptionally consistent with terminology and framework.

Due to the fact that this textbook only contains a few chapters (based on the stages of the lifespan such as infancy, early childhood, etc.), and is not broken down further into developmental domains (physical, cognitive, psychosocial growth), it can make it slightly challenging to identify and assign smaller reading assignments without referencing specific page numbers.

The topics presented within this textbook flow nicely, and are organized in a logical manner for the reader.

There are no interface issues within this text such as navigation issues, distortions of images, etc. I would add that some of the images included within this textbook are slightly rudimentary (black and white, with limited detail or visual interest) and may benefit from some more interesting components.

There are no grammatical errors within this text.

I would say that this is a major strength of this textbook. In my experience, many other textbooks contain a limited amount of perspectives and/or inclusion of diverse ideas. This particular book is intentional in terms of including diverse perspectives, local AND global issues, and is relevant and meaningful to all students as a result.

Reviewed by Joshua Becker, Professor of Psychology, Greenfield Community College on 6/30/20

The text itself is comprehensive, with each topic organized into logical and interesting sub-topics. The sub-topics are written comprehensively in easy-to-digest paragraphs. There is no glossary or index, however. read more

The information in this text is accurate, current, and relatively bias-free. Good (brief) section in Early Childhood on transgender kids, for example.

This text has a good balance of grand theories and current research. It will (like all texts) require continual revising as new theories emerge and new areas of focus become important for developmental psychologists.

The writing is clear and understandable.

Good internal consistency!

This is a strength of this text. Each subsection can be used on its own, or part of the whole.

Overall, the text is well organized, though I think I would prefer a text that has more layers of organization. This text has 10 chapters, each with numerous sub-headings, but without clear delineations between domains of development.

I did enjoy the interface - though this is essentially one long PDF document, which may be confusing or problematic for some students.

Nice writing!

The text includes weaves in topics related to several lenses of identity, including race, class, sexualities, and gender identity. It does not challenge, however, the enduring structures of oppression in the field of psychology and society at large - though this is probably considered outside the scope of developmental psychology.

I enjoyed the text! I would consider adapting it if I could find ancillary materials.

Reviewed by Kevin Duquette, Assistant Professor, Bridgewater State University on 6/22/20

Very clearly laid out with ten chapters ranging from prenatal to death. Table of contents acts also as an index of sorts, with specific topics within each stage clearly defined and page numbers provided. Could benefit from a glossary (either at the end of each chapter or at the end of the text as a whole) and/or separate index for concepts that are present throughout multiple chapters.

An overall comprehensive view of development with special consideration for culture and diversity. Text also discusses how views have changed over time (e.g., in relation to intellectual disabilities; gender roles, etc.), and uses the most current terms. Text also provides information on many developmental theories (as opposed to pigeonholing information to few), and continually spirals back to these topics to reinforce them. A few small errors (e.g., “tabula rosa” instead of “tabula rasa”, pg. 16), but by and large information is up to date, and clearly explained.

All information is up to date, and uses current citations. Authors also did a great job with citing and providing sources as well so that readers can find additional information on topics from the primary sources. In addition to current parenthetical citations, the writers provide context to let the reader know when the data were taken, which allows a more informed understanding of the numbers provided. Authors show data trends over time that will be easy to update as newer data are published.

One area where there could be additional relevant information would be in regards to substance use, and the recent legalization of marijuana across U.S. states and Canada, and how this legalization may affect understanding and interventions related to marijuana and other substance use.

Writing is very accessible, and clear. Jargon terms are defined as part of the text and the flow of the book as a whole is logical. Main topics (i.e., developmental theories) are revisited and applied to specific life stages with relevant examples to connect to larger themes.

Major concepts are revisited in each chapter, and examples for application of knowledge are given. Further, the formatting itself is consistent, leading to an overall clean and intuitive look. Authors are also consistent with the use of discussion questions for each chapter.

Very well organized. Great use of headings, subheadings, bold, italics, color, and other formatting to break up ideas into intuitive sections. The chapters are broken up logically based on developmental periods. Could have benefited from additional focus specifically on early adolescence considering the importance of this stage of life (relative to others—similar to how the text broke up childhood into early ‘childhood’, and ‘middle & late childhood’)

Clear organization throughout. Good use of boxes, figures, graphs, etc. to enhance understanding and draw readers’ attention to important concepts or illustrations. Logically sequenced chapters and sections.

Very well-organized and good use of images/charts to enhance understanding. Text provides links to images, graphs, references for further reading, which enhances the interactivity of the text. Text would benefit from the ability to “jump” to chapters or sub-sections by clicking on that particular section in the table of contents.

Aside from the aforementioned “tabula rosa” being used instead of “tabula rasa” (p.16), this book reads well and is grammatically sound.

Shows appreciation and consideration of the effect of culture and intersectional identity on development. Provides international perspectives on development as well. The only criticism would be that the vast majority of the images used are of white people.

Solid text. Rivals books that are $100+.

Reviewed by Sandra Gilliland, Associate Professor, Louisiana State University of Alexandria on 4/20/20

This 468 page book covers all of the major stages and domains of development. The book begins with a detailed overview of the field of lifespan development and then goes into great depth on the common issues and areas of interest for each major... read more

The book appears to provide information from various perspectives allowing the student/reader to apply critical thinking to evaluate each topic.

This book was published in 2017, the majority of references are less than 10 years old. The topics are covered with several recent examples but also uses many of the historically popular studies that will remain relevant (for example Harlow's work on attachment).

This was actually my favorite part of the book. I found it very easy to read and feel as though my students would as well.

The book builds on some of the most reputable theories in lifespan development (Piaget, Erikson, Vygotsky).

Modularity rating: 3

I like that each stage of development is covered in separate chapters but it also results in very long chapters. For example chapter 3 is 44 pages long. That is a lot for students to digest so I would need to assign page numbers instead of chapters.

I like the breakdown of chapters into the developmental stages.

The book downloaded as a free PDF, no problems navigating.

No issues with grammar were noted.

Text and images appears to represent a wide arrange of different cultures.

The length of this book is a little intimidating but the content is excellent.

Reviewed by Masami Takahashi, Professor, Northeastern Illinois University on 4/5/20

This is a very comprehensive Lifespan Developmental Psychology textbook (465 pgs). It covers not only psychology but also a fair amount of biology as well, and almost any other topis I can think of including relatively up-to-date research findings. However, one may say that it is good for neither one thing nor the other. Although comprehensive, this book lacks details in theory and data for upper level Developmental Psychology courses for our Psych majors. The book simply scratches the surface of many topics. On the other hand, there is simply too much information for our Gen Ed Human Development. What this means is that the instructors are required to work quite a bit before adopting it for a particular course, at least initially (e.g., finding supplemental readings for our majors, selecting small portions of this textbook appropriate for our Gen Ed students, etc.).

It is accurate for the topics it covers, but the discussions are often limited in details for the Psych majors.

Content is relatively up-to-date. However. with any textbook with cutting-edge research evidence, it is inevitable that that part of the book will require further editing in the near future.

It is clearly written and readable for any level of undergrads.

I noticed several sections with duplication (i.e., cut/paste) that needs editing

For those instructors who are adopting a part of this book (e.g., easy sections for Intro Developmental), it would be helpful if the subsections in each chapter were numbered (2-1, 2-2, etc.) so that they can be specified in the syllabus.

Organization/Structure/Flow rating: 2

I like the fact that the References are provided not at the end of the book but immediately after each chapter. This allows the readers an easier access to the references if needed. Personally, however, I prefer a topic by topic (rather than chronological) arrangement of the chapters.

There are lots of Figures (mostly photographs from public domains) throughout the book that do not have any caption. I couldn’t tell what these pictures were for.

Good. Readable.

It includes a fair amount of cross-cultural studies

Having presented pros and cons above, would I adopt this book? Yes, I would for my Gen Ed course. That means after thoroughly reading this book, I have to handpick those sections that are general enough for the freshman/sophomore students, specify the pg numbers in syllabus, and align the contents with the exams that I already have for the course.

Reviewed by Linde Althaus, Psychology Instructor, Minnesota State University System on 3/8/20

This book covers all of the age groups covered in a lifespan class, but consolidates some age groups to lengthy chapters. read more

This book covers all of the age groups covered in a lifespan class, but consolidates some age groups to lengthy chapters.

The book appears to be straight-forward and accurate. Several topics could use up-dating and it surprised me that it was last updated in 2019.

The photos seemed dated and some of the topics could be refreshed, but it did not impact my perception of the book as a whole.

Topics were clearly written and were approachable to a reader.

The writing and terminology appears to be consistent throughout the text.

The chapters were long and I feel like it may be difficult to divide into modules. I'm not sure how I would assign the readings in a fully online class if I adapted this text.

This is a book organized from birth to death, which is how I like to teach Lifespan. Someone who teaches a topical approach would struggle using this text.

You have to scroll through the text to find your page. There are not easy ways to jump to various sections of the text. I wanted to read particular sections that I feel are my areas of expertise and I found it cumbersome.

What I read appears correct and well-written.

Some of the pictures are culturally diverse, but I would like more examples and descriptions of other cultures within the text.

I appreciate that this book is available, but I am hesitant to adopt it at the moment. If it was updated, made easier to navigate and more cultural diversity was added, I would definitely switch.

Reviewed by Pamela L. Parent, Associate Professor (Adjunct), J. Sargeant Reynolds Community College on 1/14/20

The text was comprehensive and well-planned. Addresses major concepts and theories with numerous online links to facilitate further inquiry. read more

The text was comprehensive and well-planned. Addresses major concepts and theories with numerous online links to facilitate further inquiry.

Accurate content with good coverage of material. Commendable addition of inclusion of some “nontraditional” areas in developmental psychology.

Good use is made of numerous and diverse live links allowing readers to access various resources.

Written in a clear and coherent manner with some excellent examples. Content was presented in a manner that made it useful to varying levels of learners.

Chapters are well-structured and organized in a clear manner throughout.

Chapters contain logical sections with subheadings. Developmental Psychology lends itself well to a chronological format as used in this text.

Well-organized with consistency in addressing domains. Chapter sections well-segmented.

This text worked well with the online format. Contains numerous helpful graphs, diagrams, etc.

Grammatical errors were not apparent however a few spelling errors that one would hope would have been caught on review - “constructivitst’ and “constrctivist” in the same sentence cluster.

This book consistently incorporated attention to diversity. The unique influences of various cultures on developmental stages was well-addressed.

A comprehensive textbook that works well as an OER. I am intrigued by the possibility of using this as my primary text.

Reviewed by Elizabeth Becker, Senior Instructor II, Eastern Oregon University on 1/4/20, updated 1/15/20

The text covers a wide range of topics related to development, including current trends and issues. read more

The text covers a wide range of topics related to development, including current trends and issues.

The text is accurate and includes a large number of references. It also includes important critiques of major theorists.

The structure of this text will allow it to be easily updated and continue to address important trends and issues.

Educational Psychology texts are often written with dense academic language that makes it a challenge for students to easily process and understand. This OER is written in a way that makes the information more accessible to students and will help keep their interest.

There is a consistent format and structure used throughout the text.

While the overall organization of the text is through chronological age, each chapter addresses many of the same topics in a way that would make it easy to focus on specific topics across different ages/chapters.

The text follows a consistent and logical organization.

The material is presented in a fashion that makes it easy to read and navigate.

No major grammatical errors or patterns were detected.

This text specifically addresses cultural differences related to the topics at hand in a way that is respectful and will help anyone working with a variety of cultures in the classroom.

Reviewed by Amy Hammond, Associate Professor/Dept Chair, Centenary College of Louisiana on 12/30/19

Very comprehensive! All the major concepts and ideas are addressed, although sometimes briefly (as is necessary in a lifespan text). read more

Very comprehensive! All the major concepts and ideas are addressed, although sometimes briefly (as is necessary in a lifespan text).

On the whole, the content is accurate and consistent with most developmental texts. There are elements in the pre-natal development section (particularly around teratogens) that I do not believe are fully up-to-date and provide inaccurate or misleading information.

Content is highly relevant to the topic. While there are some topics that some would consider “supplemental” throughout, there is enough variety that individual instructors can tailor inclusion of these materials as they desire.

Material is presented in a clear and coherent manner throughout the text.

The structure within in chapter reflects consistent approaches to the material. The writing and thoughtfulness is consistently strong throughout.

Organization and structure lend themselves to including or excluding various elements as one chooses. Major sections are easily identified and segmented.

The overall organization is very good for a chronological developmental text. Within chapters, there is a consistent organization of physical, then cognitive, then psychosocial issues and within these sections, when relevant, consistencies in the order of presentation of theories and concepts.

Learning Objectives in each chapter were clear, if exclusively at the lower levels of Bloom’s Taxonomy. I found the use of headings within chapters to be difficult to follow. It wasn’t always easy to see which sections where sub-sections of which ideas. Overall, this text is less visually “fun” than the big publisher versions, however, it is full of colorful photos, relevant graphs and diagrams.

Excellent! This text is easy to read, but is still written in an appropriate manner for lower-level college students.

There is excellent coverage of ideas for a United States audience relevant to US-centric concerns (for example, there are very good sections on LGBTQIA issues). However, mention of topics outside a US context are somewhat thin (especially in the first half of the text). To be fair, this reflects weaknesses in the field more generally (which are slowly being rectified). There is more comprehensive consideration of cross-cultural issues in later chapters. The prenatal development section felt somewhat maternal-blaming. While there were some explicit mentions that environmental factors were important, there was strong implication that most things which could go wrong were the “fault” of the mother. Nothing was explicitly stated in this way, but I felt there was too little explicit and implicit acknowledgement of the randomness that can sometimes cause less-than-ideal outcomes during pregnancy and birth.

I am grateful to our colleagues who have worked to put together this excellent resource! And in particular that you have chosen to make it available in a way that invites ongoing use/changes/updates! It allows me to use the many, many, MANY wonderful elements and tweak the few things that are not quite my personal pedagogical approach. I anticipate adopting this text next year!

Reviewed by Sara Fier, Professor, Minnesota State University System-Southwest Minnesota State University on 12/30/19

The book provided good coverage of developmental psychology concepts. There was no index or glossary included, although the fact that the book is in an electronic format makes this less problematic than for a hard copy book. read more

Comprehensiveness rating: 3 see less

The book seemed to present information accurately and presented multiple theories/perspectives on topics without getting too technical/detailed.

The book covers developmental psychology historical information and developmental basics well. More recent research is incorporated as well. The book's format seems to allow for updates to be easily made.

The book is easy to understand. In some cases illustrative examples help explain concepts that may be new to the reader. The reader would benefit from the use of additional examples.

The book's internal consistency is good, with chapters being organized in a similar format.

Developmental psychology allows for ease of modularity, and this text uses a chronological lifespan format.

The book was organized in the typical developmental psycology chronological format and then further broken down within each chapter by developmental domain: physical, cognitive, social. That was easy to follow. As future editions of the book lead to revisions within each domain, domain-specific organization and transitions can be reconsidered.

Navigation of the book was easy and seemed to work well in the electronic format. No display issues were noted.

Grammatical Errors rating: 3

The book had grammatical/typographical errors comparable in number to published textbooks.

A variety of examples were provided related to diversity of race, ethnicity, and background. Authors should continuously strive to enhance incorporation of these topics into books.

I appreciate the authors making this book available. I look forward to using it as a devopmental psychology text.

Reviewed by Diane Bordenave, Associate Professor, SUNO on 11/9/19

The text covers lifespan development content from birth until death. There is an Table of Contents with chapter sections and page numbers for reference. read more

The text covers lifespan development content from birth until death. There is an Table of Contents with chapter sections and page numbers for reference.

I found no grammatical errors, bias or inaccurate content.

The content of the textbook should become more and more relevant as the country recognizes the importance of understanding and responding to the needs of an aging generation of baby boomers. For the most part, content has been more focused on early childhood and infant development. When comparing the content to older lifespan development textbooks, I did not see many issues where changes in a short period of time were necessary for updating the text. For the most part, issues of development covered here have remained relatively unchanged over time. Particularly in an introductory survey course, more in-depth analysis of changes and consequences such as those resulting from science or technology, are not expected here but can be further explored in graduate or higher level specialized courses on a topic.

The textbook is written at a level appropriate for the students at my HBCU, many of whom are first generation college students. Terminology, when used, is defined. Figures and Tables assist in interpreting the prose.

The terminology and framework in the text is internally consistent and is particularly suited to a lifespan approach. It helps to understand the continuity of life from birth to death and how earlier stages of development impact later ones when the terminology and framework are consistent.

I would have preferred that the text was divided into more chapters than 10 to better align with a typical semester of 15 weeks. Students tend to understand and work better on a chapter by chapter basis than on subsections in my experience.

After a well written introduction, the text presented the chapter is a logical fashion that followed the normal human developmental process from birth to aging/death.

I was able to both view the textbook online and download it and make a copy. I had no interface, navigational or display feature problems in either context. I intend to offer this textbook in an online format.

I found no grammatical errors, and I am a stickler for that in the academic setting.

I teach at an HBCU with mainly non-traditional students so cultural sensitivity is important to me in choosing content. The cover of the textbook is of a diverse family which is immediately welcoming. In the chapter are other culturally diverse images such as in Figure 1.1.

I have adopted this book for my Spring 2020 course CDFS 303 Lifespan Development in the Family. I am happy to give the students the benefit of not having to purchase an expensive textbook, which many of them were unable to do, and still benefit from the readings. I have recommended this book to my colleagues as well.

Reviewed by Sarah McEwan, Assistant Professor, Marian University on 11/4/19

This text addresses all aspects of human growth and development that I cover in my course. read more

This text addresses all aspects of human growth and development that I cover in my course.

This text is accurate up to its published date, 2017.

Published in 2017, so relatively up to date, but there's always few opportunities for updates here and there.

This text is quite user friendly and quick to read.

The text has solid internal consistency.

This book covers all the basics, but just the basics. This text does not contain a lot of additional fluff that other texts contain.

This text was well organized.

No issues with navigation.

I found no grammatical issues.

The text does a fine job covering the basics, but the field of psychology in general has a ways to go to become inclusive.

I chose this text for an accelerated course- I needed a book that accurately and concisely covered all my key concepts, which this did. However, this text did not have as many opportunities/ asides to provide further reading for students interested in specific areas as I have seen in other textbooks. If you are looking for fluff, this is not your textbook. However, I intend on continuing to use this text in my accelerated classes, as it was perfect for a quick overview that my students could manage in a short amount of time.

Reviewed by Allie Chroust, Assistant Professor, East Tennessee State University on 4/21/19

The textbook covers human development across the lifespan. It is presented in the chronological framework. Each chapter provides an in-depth look at that stage of development. However, there is no glossary of key terms or index. Students would... read more

To the best of my knowledge, the information presented within the textbook is accurate. The one area for improvement in relational to accuracy would be the updating some of the sections to use more inclusive terminology (e.g., Children with Disabilities, p. 176).

The textbook is was last revised in 2017. I did come across one or two content areas that should have been updated for the latest edition (e.g., Box 2.3 on p. 50--the Tennessee Law has since been changed; Figure 1.18 p. 2006--it would be very easy to update the years on the basic figure as the years do not relate to any specific study it is simply a schematic of research design).

The textbook is written at a level that lower-level undergraduate students can understand.

Terminology and framework is consistent throughout textbook.

The text is divided into 10 chapters. There are subsections within each chapter if the instructor wishes to break up readings assignments into smaller chunks.

Chronological presentation of human development.

Textbook is easy to navigate within your PDF reader. Tables and Figures are clear. Each hyperlink I tested within the textbook worked properly.

No to minimal grammatical errors.

The textbook does an adequate job describing that human development occurs in variety of contexts, one of those contexts being culture. However, the textbook could provide a more in-depth description of the impact of culture on various developmental concepts. For example, the textbook frequently states, "in some cultures, ...." but, more often then not, textbook does not describe the different patterns of behavior or specify what culture is being referenced.

It is great to have an open textbook aimed at lifespan development however I would like to see a few improvements to make it more competitive against the ebooks for-profit publishers are providing: 1) glossary of terms and/or definitions in the margins 2) improved figures and creation of figure captions 3) inclusion of examples of applications of concepts that show students how the information can be directly applied to various careers 4) hyperlinks within the text--for example if students click on one of the learning objectives at the beginning of the chapter, they are taken to the section of that chapter that addresses that specific objective. 5) inclusion of reading comprehension questions for students to check themselves on before moving on to next section.

Reviewed by Patrick Smith, Associate Professor, Thomas Nelson Community College on 3/21/19

The comprehensiveness of the textbook is interesting, as there are only ten chapters. In other words, the authors pack a great deal of information into each chapter. This book covers all of the requisite topics for an introductory or survey... read more

This is an introductory level textbook, so specific research found in higher level courses would be missing. For the most part, this text covers the basics well, and any inaccuracies are negligible and can be overcome with good discussion.

The thoroughness of the coverage, which is a strength, makes this text very relevant to get a good discussion of actual human development going.

This textbook is very easy to read and follow. Any technical terms and theoretical concepts are well defined and illustrated within an applicable context.

There is no real individual psychological perspectives evident here beyond the basic introduction to this context of human psychology. For this reason, all areas of the human lifespan get fair coverage and presentation.

With a lifespan development course, it is easier to present material that can be discussed as physical, cognitive, or socioemotional. This textbook is divided by stage of life alone. For this reason, it may be difficult to separate chapters into smaller reading sections easily.

The text follows a nice, logical pathway through the human lifespan with a pretty strong connection between stages of development.

Technically, the presentation of the textbook comes without flaw.

There is no consistently evident problem with grammatical errors.

There is a pleasant focus on diversity and inclusion in both the text and the illustrations. There is some attempt to apply the principles discussed beyond the dominant culture of America, without this being forced and artificial.

I would highly recommend this textbook for an introductory, 200-level developmental psychology course. It hits all the right points and is engaging enough to stimulate some good class discussions.

Reviewed by Natalie Danner, Assistant Professor, Western Oregon University, Open Oregon Educational Resources on 3/20/19

This textbook is VERY comprehensive and covers lifespan development from prenatal development to death and dying. There is a very detailed Table of Contents; making it easy to find age groupings, theories, or concepts in development. There is no glossary, which would be helpful to find mentions of a specific term. Overall this textbook covers a great deal of material, without delving into the topic of atypical development.

The developmental theories and definitions were accurate.

Most of the content is still current, and the publication dates for this text is 2017. However there is an emphasis on Howard Gardener's Multiple Intelligence theory in Chapter 5 which has much research against it currently. Rather in the field we now advocate for more of a Universal Design for Learning (UDL) approach or a multi-sensory/hands-on approach to learning. Neither of which are mentioned in the text.

This text would be easy to read and accessible for an undergraduate course in child/adolescent/lifespan development.

Yes, this text is internally consistent.

I plan on using only several chapters of this textbook for a focus on child development ages 3-elementary; chapters 1, 4, and 5. These chapters do make sense on their own and will work as good content for my child development course. However, I wished that the theories that were mentioned, a few in each chapters, either could have all been combined in one chapter, or were easier to pull for individual readings for an online course.

Other than the theories, the book moves in a linear fashion from prenatal development to death and dying. Theories are interspersed in a variety of chapters.

It was easy for me to navigate through the textbook. Images and charts were clear.

This textbook used accurate grammar and writing conventions.

Cultural Relevance rating: 2

The book does not mention cultural diversity, cultural bias, diversity of children and families, and other key topics needed in a child development text. Supplemental material will be needed to focus on this subject.

Reviewed by Laura Lawn, Adjunct Faculty, Chemeketa Community College on 3/5/19

On the whole, the book is very comprehensive, though there were a few places where it could have used a bit more. I did not see much on atypical development outside early childhood years which would be beneficial to include. It would also be nice to see a wider range of cultural studies. The text does not utilize a glossary, but the words are defined in the chapters and you can search the document if using as an e-book to find words which is even easier than a traditional glossary. Though if a student wants to print out the text, a glossary would be helpful.

This textbook is a straightforward discussion of human life span development which, as a field, is always growing. This book is largely current and accurate, but there should be updates as some references are older. Though the information is presented without bias and with references for further research.

The book is current and mostly up to date (as of 2019), though some of the references are a bit old. It worked when the authors were using the original work for a theory but other sources could be updated. For example, the media and development section didn’t touch social media. Including some of the newer studies would increase relevance to the technological age we are in.

The text is clear, easy to read, and understandable while still providing in-depth information. The graphics helped to clarify ideas, especially when explaining or comparing theories.

The look and feel of the text hold consistency through the document. Chapters were presented with continuing themes (such as Erikson’s stages in each life stage) and all work is referenced.

This text is sectioned into logical chunks that can be taught individually or in conjunction with each other. You do not need to read one chapter to understand the following one meaning the book could be taught any number of different ways to match with a variety of courses.

The book is organized into age periods, which is the way I think about the course information, though not the way I have always seen it presented in a text. So, the overall organization matched my thinking quite nicely. This organization also makes it easy to break the text into sections if the entire life span is separated over multiple classes (for example, if someone taught birth through adolescence only).

The text is pleasant to look at with calming colors and a variety of images and graphics that represent cultural diversity. There are no digital or navigational issues with the book.

I did not find any grammatical errors or issues.

The text is not offensive or insulting to any group and handles discussions of differences well. There are some representations of cultures and ages, though this book would benefit from a wider range of faces in images and of experimental studies conducted by / for nonwhite populations.

Reviewed by Francesca Kendris, Associate Professor, Bloomsburg University of Pennsylvania on 2/27/19

The book is quite comprehensive. It addresses all developmental milestones and the major theories that accompany them. It provides appropriate depth to each topic and offers a thorough explanation of the subject. The book does not possess an... read more

The book is accurate, error-free and unbiased. It is a straightforward presentation of Lifespan material in and objective and researched light. There are references at the end of each chapter to support the context of the text. There are no attempts to persuade the reader into to thinking that there is a correct or incorrect way to think about the material presented in each chapter. It is factual and the facts are supported by multiple references in most cases.

Relevance/Longevity rating: 3

The content is currently up-to-date (as of 2/2019). There are a variety of references provided for the material presented. Some of the references are current and some are rather dated. In some cases the authors went to the original source for a theory or study, which is fine for most clearly presenting the idea; however, at other times the references for material in the text were from the 1980's or 1990's and could soon be or already be considered obsolete. On the bright side, the material is written in such a way that it should not be difficult to up-date this text with more modern references throughout the book.

The book is very clear and written in easily understandable terms. Everything is defined and explained in a thorough manner for most undergraduate readers. Yet, it is sophisticated enough that I am planning on adopting it for my graduate human development course. This is because while it defines most terms and explains most theories, it does so in such a way that it provides enough depth to substantiate the theory or term presented.

This book is presented in order of development from pre-birth to old age and dying, touching upon milestones and developmental considerations along the way. It is internally sound and all work is referenced and themes are carried from chapter to chapter. For example, Erikson's Psychosocial Stages are presented in each chapter, as well as physical aspects of development. As noted earlier, all terminology is supported by referenced material which addes to the structural integrity of this text.

The book is readily divided up into different modules. One chapter is not dependent upon the next for a thorough understanding of each stage of development. The book could be assigned in any order without difficulty or too much self-referencing.

The book is organized in the most logical fashion for a developmental textbook: from birth to old age. It breaks down into the following chapters: An introduction; Heredity, Prenatal Development, Birth; Infancy & Toddlerhood; Early Childhood; Middle & Late Childhood; Adolescence; Emerging and Early Adulthood; Middle Adulthood; Late Adulthood; Death & Dying. It is free from technical jargon and presents material in a logical and understandable manner.

The images and diagrams in the text represent diverse populations in terms of age, gender, race and LGBTQA populations. The images and diagrams enhance the text and are pleasing to look at.

The book has excellent grammar and is free from typographical errors.

The text is not culturally offensive and the pictures are very diverse. The text itself makes good references and is inclusive of the LGBTQA populations. There are not too many other diverse populations represented, apart from age and gender. There are some considerations given to racial and ethnic differences but not enough. The book would benefit from more multicultural references.

Reviewed by Dan Bacon, Lecturer, San Diego State University on 2/22/19

The courses I teach primarily cover birth through middle childhood, so my review focused most heavily on chapters 1-5. The text is comprehensive in that it covers a wide range of topics you would expect in such a book. However, it may be improved by providing more depth in many of the areas. Even for use in a broad survey course, it would be nice to have more examples to help students understand the basic concepts they are reading about. For example, when covering longitudinal research, I might expect the author to mention an example of landmark longitudinal research in the field. There are certainly some examples (e.g., mentions Piaget when discussing case studies), but not to the degree I'm accustomed to in other textbooks. This text would also benefit from a glossary. While an eText allows students to search for terms easily, for those students who print the pdf (for preference or issues of accessibility), a glossary would be helpful.

A few errors stood out, and makes me imagine there are others in areas outside my expertise that I did not catch. One small example is the author lacks accuracy in stating: "Although the behaviorists were incorrect in their beliefs that it was not possible to measure thoughts and feelings". This is a misunderstanding and oversimplification of Skinner's analysis of public versus private events. Skinner, and other subsequent radical behaviorists, welcomed the scientific analysis of private events, and noted each individual is the observer of their own thoughts. The view that private events have no place in science was that of Watson and the methodological behaviorists. Being a half century past the shift to radical behaviorism, it may be time to start representing the field of behaviorism more accurately.

Mostly relevant with many 2016 citations. As a 2017 publication however, I would have expected the author to use more up-to-date data in some areas. For example, the author referenced a 2012 CDC publication with autism prevalence data from 2008 (1 in 88 children in US). It would have been more relevant to use 2016 publications which showed CDC prevalence rates were then 1 in 68 children in the US. With that said, the text is written in a way that could be easily updated (2018 publication of CDC numbers estimate the prevalence of ASD to be 1 in 59 in US).

I believe students would enjoy the clarity of this text, in terms of its concise writing. This text does a nice job of avoiding jargon, or clearly explaining the terminology when it is used. Where I think it could improve is in providing some additional examples to illustrate some concepts. Additional figures or links to videos might really benefit readers in their ability to quickly digest material.

There seems to be a clear framework that is easy to follow across all chapters. The text is easy to navigate in terms of its internal consistency.

This text could be used in a modular fashion. I could easily see taking chapters 1, 4 & 5 to use in my course on early and middle childhood. One area that adversely impacts modularity, which I touch on in the organization section as well, is how the book covers individuals with disabilities. For example, discussion of ASD is self contained in the chapter on early childhood. While the author briefly touches on the ability of adults with autism to live and work independently, this would be missed if using a modular approach of only assigning the chapter on adulthood.

As is typical of many other human development texts, the author does a nice job of consistently referencing hallmark theories (e.g. Erikson's stages of development) across the chronological chapters. This allows for the reader to build upon prior knowledge, but is done in a way that doesn't limit modularity too much. One area for improvement would be looking at atypical development and individuals experiencing disabilities across all chapters. Discussions of lifelong disabilities, such as Down syndrome, tended to be concentrated in early chapters, without touching on how individual's lives might be impacted in adulthood. This tends to be a problem with other human development texts as well, where atypical development is treated more as a token issue, often as a standalone chapter.

Images and charts are all clearly displayed in the pdf. While navigation could be improved by including links to more outside sources, or the ability to easily jump between chapters and topics by clicking on the index, there are no significant interface issues. I think users of eTexts have come to expect them to be a little easier to navigate through internal links between chapters or to a glossary (if it had one).

Grammatical errors did not strike me as an issue when reading this text.

While no text is perfect, as described by some other reviewers, I found myself wanting a greater focus on diversity. It would have been nice to see a focus not only on issues of race, ethnicity, and sexual orientation, but also on topics like military culture, immigrant culture, and disability culture.

Overall, I found this to be one of the strongest OER options for human development I've come across, at least for an undergraduate survey course. It is easy to think about topics that could be enhanced, such as cultural perspectives, but I think it is worth remembering that there is a finite amount of content that can be covered in one semester. No one text can meet the needs for all courses in developmental psychology or human development, but I thank the authors for creating and sharing something that likely fits the needs for some course very well.

Reviewed by Jennifer Parta-Arno, Psychology Instructor, Minnesota State on 2/7/19

Overall I found this text to be very comprehensive in covering all of the developmental stages and topics that I have used in other textbooks. It has a good layout of information that is for the most part relevant and up to date. read more

Content Accuracy rating: 3

I found at least one instance of out of date information- in Chapter 2 it discusses the law that went into effect in Tennessee that women who use drugs while pregnant can be charged, however that bill was allowed to sunset in 2016 and that is no longer the case so this is outdated information. Hopefully this OER text will be reviewed regularly and updated.

I noticed that in discussing Children and The Media in Chapter 4 there is but a brief paragraph or two and it only pertains to tv not social media or any devices such as smartphones or tablets which are a huge topic of developmental discussion. Also, I do not see any mention of social media and it's influence on teens in the chapter on adolescence. Would need to provide up to date and supplementary materials.

Yes I found the text and writing to be very precise, clear and easy to comprehend for students. Didn't seem to be too much terminology and if used it was defined pretty well.

Yes the layout and structure in which material/theories were covered was consistent throughout the text. The reader knows what to expect in terms of presentation and formatting.

There are quite a few sub-headings and divisions or modulations within the chapters. It isn't the easiest to "pull out a chunk of material" because of the pdf formatting. Would prefer linking to different sections.

I found the text to be fairly well organized.

I just have to say I am not a fan of the pdf format. I have used several other OER texts and they all have the ability to link to different sections within the text or chapters and you can present by Chapter instead of directing someone just to a certain page/chapter. As a hardcover book that is fine, however, I think that online users are expecting more functionality. Also, there aren't any links to supplemental videos, articles or activities which is another aspect that needs improvement.

Grammar was fine.

I appreciated the section on cultural differences in end of life decisions in the final chapter. Also, the section on gay and lesbian elders was refreshing to see included and something that is not currently in a text I use. I liked that!

Overall it is an ok option if you just essentially want an ebook, however as I stated above I think other OER resources have a lot more functionality than this text which is in a pdf format. Not very user friendly and wouldn't be my first choice to use for my students.

Reviewed by Lori Waters, Lecturer - Adjunct Faculty, Leeward Community College on 1/24/19

The research and experiment chapter was easily readable, attractive and enticing. Good, solid, well rounded text. I will highly recommend this text. read more

The research and experiment chapter was easily readable, attractive and enticing. Good, solid, well rounded text. I will highly recommend this text.

The content is accurate. A bit of bias is felt. However, due to readers biases the authors did a good job of masking biases with good solid research that was sited and created unbiased accurate content.

Graphics and photos are helpful and are nicely relevant and certainly adds great clarity. The text easily blends the valid content and includes relevant updates that flow nicely. Organized to easily create new updates. Epigenetics could have been more thoroughly covered.

The text is written with excellent clarity with a simplification of jargon that makes material easy to grasp quickly.

The text is consistent, with topics flowing together and broken up into easily readable subheadings, and tables/graphs/charts/images all flowing nicely. Terminology is consistent.

Good modularity which is consistent throughout the text. Subheadings are clear, easy to read and flow nicely to the eye. Self-referential is not present. Text is easily divisible into smaller reading sections that make it easy to grab topics out of their context. Modularity is also well balanced with the flow, fluidity and relatedness of previous subunits. Especially good flow for online reading and easy page accessibility.

It is easy to page up and down and clearly see the logical organization, again especially as an online pdf. The organization is excellent!

The charts, images, photos and graphics are free of distractions regarding interface issues. They are nicely placed and spaced throughout the text and fall appealingly on the page. Easy for the eye to track and to organize.

The textbook is grammatically correct.

Love the picture on the cover! Great start. Excellent examples that are culturally relevant, especially in the “classroom” section of chapter 5 and remain consistently exceptional throughout the text.

I will use this textbook the next opportunity I have to teach Human Development with the option of choosing which text to use!!!!

Reviewed by Glinda Rawls, Associate Professor, Western Michigan University on 12/14/18

Much of the content presented in the chapters is standard for most lifespan development textbooks. read more

Much of the content presented in the chapters is standard for most lifespan development textbooks.

I did not notice many errors, however there were places in the the textbook where the authors clearly presented their bias. For example, in chapter 4 when discussing childhood disciplinary practices the authors only discussed the harmful affects of corporal punishment; however, there are other scholars who have highlighted the benefit of such disciplinary practices especially among different cultural groups. Both perspectives should have been presented.

In some areas, the content was not up to date. For example, in chapter 10 which contains information about death and dying the authors only mentioned that in 1997 Oregon had laws which facilitate dignity in dying where patients can choose to die on their own terms. However, since 1997 I believe there are three states (California, Colorado, and Hawaii) and Washington DC who all have passed these laws. This needs to be updated in the textbook. Also in chapter 8 the authors really did not discuss how women are delaying marriage and child-bearing along with the content related to marriage. And the information on marriage could have included more topics related to cultural diversity because African American women tend to have the highest rates of being single than other ethnic groups. This was left out of the textbook. Another omission was in discussing maternal mortality. The authors only cited PID as the cause for infertility but PCOS and endometriosis are two other conditions which could contribute to infertility in women. So the authors should update this too.

The textbook was written in clear and uncomplicated way. The information presented in this textbook is succinct and brief which may make undergraduate students more apt to read this textbook. It was very simple and easy to read.

I really liked how the authors used Erickson's lifespan development across several chapters. I have used other lifespan development textbooks that followed this same format. This consistency allowed the reader to have easy access to the theory so that they could apply it to various stages of development.

Each chapter had several subheadings and headings. The material was arranged in such a way that the content flowed very well. The subheadings made sense and were relevant to the larger headings.

The chapters followed the normal stages of development and were well organized.

I am not sure if this would be possible but it would be helpful if the reader could click onto the chapter and just pull it up. Since the document is in a pdf format, the reader has to scroll up and down if they wanted to move back and forth in the textbook. This was a bit cumbersome.

I did not notice any grammatical errors.

The authors made an effort to include cultural diversity and LGBT issues in the textbook. I certainly applaud their efforts, but in some ways things fell a little short in this area. For example, issues of adverse childhood experiences was not mentioned. Social issues like poverty, childhood homelessness and incarcerated parents were also omitted. It seems as though the book could also benefit from including some sociological perspectives to deepen their attempts to include diversity. They also did not include all types of families in chapter 5. They did not include trans-racial adoption or multicultural families where the parents are of different races. So the area of cultural diversity could be enhanced.

Overall this textbook would be useful in a undergraduate course. The instructor would definitely have to supplement the materials to include content that is not only up to date but also includes more sociological perspectives in understanding lifespan development.

Reviewed by Jamie Nordling, Assistant Professor, Augustana College on 11/18/18

The book content matches what I currently teach. read more

The book content matches what I currently teach.

I did not find any big errors. They do discuss how the Attachment Q-Sort is a solid, contemporary way to measure attachment, but there are issues with this method.

I did not notice any issues with relevance.

The prose is clear and easy to understand.

Consistency rating: 3

There are some topics that are not discussed enough (e.g., temperament), and some topics that are not even developmental in scope that are covered in too much detail (e.g., components of memory).

There are subheadings.

Organization/Structure/Flow rating: 3

There are several chapters that seem choppy (i.e., the sections stand alone and are not well connected).

I had no issues.

Nothing stood out.

Culture is covered, but I believe it could be covered even more.

Overall, I believe this textbook provides a good overview on human development. The writing is well-suited for introductory students.

Some of the concepts that were included that stand out in a positive way include: (a) a good description of how the field has changed from just looking at childhood to looking at the whole lifespan; (b) the use of the multidimensional, multidirectional, multidisciplinary, multicontextual, and plastic approach to development; (c) the inclusion of a description about archival data/secondary analysis, because a lot of developmental data is longitudinal; and (d) the theories of aging (i.e., why do we age).

Some of the more minor issues include: (a) There were some structure issues. I think some of this could be solved by including more clear headings or including an outline of the topics that would be covered in each chapter. It does feel a little like, “Here’s everything you need to know about this age,” without good transitions or an understanding of how topics are related to one another. Students may struggle with processing all of the information as it is presented. (b) There were some citation issues. I want students to have good models for their own writing. There were several sections of the book that made claims about research findings without a single citation. As examples, SES was linked to poor health and various other outcomes (p. 11) without a single citation. Also, the section on genetics (Ch. 2) does not have enough citations to support the claims stated. This citation issue was not found in every chapter – some sections were better than others—but it happened enough to where I took notice. (c) I would ideally like more discussions of culture; however, the book does talk about some aspect of culture in every chapter. (d) There were some topics that were discussed in too much detail given that the topics are not inherently developmental. For example, the authors go into a lot of detail about the different types of memory in chapter 4 (e.g., discusses rehearsal, different types of declarative memories) and into a lot of detail about sex in chapter 7 (e.g., phases in sexual response cycle, role of the hypothalamus, STIs). (e) And there are some topics that, while they may be developmental, are described in more detail than I have seen before in a developmental textbook. For example, (a) there was more detail than other books on prenatal development, pregnancy, and childbirth;(b) I have never seen as much detail about Piaget’s theory in any textbook (not even a child development book that has more time to focus on Piaget); (c) there was a lot of detail on sports and sports involvement, and (d) the sections on childhood issues (e.g., genetic disorders, childhood disabilities, communication disorders) were too detailed given that they seemed more biological or medical than psychological. Note that I am not saying that these issues do not have psychological components, but rather that that is not the way they are presented. They’re presented simply as biological/medical descriptions. (f) There were also some topics that were not detailed enough. My biggest area of complaint in this area relates to temperament. The authors spent too much time focusing on Thomas and Chess, which we know is an outdated view, and spent very little time talking about contemporary approaches to temperament or children’s personality.

Some of the more major issues include: (a) One of the things that bothers me about this textbook is that there are VERY few critical thinking questions that lead students to think deeply about the material. Of course, these questions can be addressed in the classroom, but the book does not include any real aspects of active learning. (b) I wish the textbook had more “science” built into it. The introduction sets up the field as scientific, but there is often little discussion about how the scientific method is essential to the findings presented. Chapter 3 stands out as doing this better – there is more incorporation of research methods, study findings, and some issues with measurement – but other chapters were deficient (c) Relatedly, given that I am teaching my lifespan course in a psychology department, we talk about how developmental psychology is much more than understanding the “whats” and the “whens” of development. We really are aiming to uncover the “hows,” “for whoms,” and “under what conditions”. Essentially, I want my students to better understand mechanisms. This book, compared to about five others that I have either used or previously reviewed, seems to talk more about the “whats” and “whens”, and in my opinion, these are less psychological. For example, topics like (a) when to introduce solid foods, (b) toilet training tips, (c) healthy eating, and (d) how to choose between preschool programs seem more suited to students who are taking a child development course in high school rather than students who are pursuing the scientific study of human development. I realize that this may have been the goal of the authors – perhaps they wanted their textbook to have flexibility for different types of courses. For me, this takes away from the messages that I tell my students.

Will I use this book in my course? In short, I have not decided yet. As noted above, the content that I normally expect my students to know (except for temperament!) is present within this textbook. However, students are not going to be asked to use their critical thinking or scientific literacy skills in this book as much as other books.

Reviewed by Lisa Dunkley, Assistant Professor, East Tennessee State University on 10/23/18

The text is comparative to other texts in the field. However, disability inclusive issues across the lifespan would add for a more comprehensive outlook. read more

The text is comparative to other texts in the field. However, disability inclusive issues across the lifespan would add for a more comprehensive outlook.

Book has used prominent literature to support context.

Information included is relevant to each topic area and today's society.

Book is easy to follow and undergraduate level students will be able to comprehend the information included in the text.

Consistent with related texts.

Book is organized into sections that make it easy to break up reading the content.

The book has a good flow and is easy to understand. Flow is consistent with others in the field.

Images included are appropriate however more vibrant images would make for a more user-friendly book.

None observed.

Book is not culturally insensitive. However more references to other cultures would make for a more inclusive book.

The book is easy to follow and navigate. Information is consistent with for sale texts in the field.

Reviewed by Christopher Belser, Assistant Professor, University of New Orleans on 6/19/18

Overall, the text covers a wide array of topics within this subject, but the degree of depth to which these topics are covered varies. Career development isn’t introduced until the section on emerging adulthood. Research dating back 50+ years... read more

Overall, the text covers a wide array of topics within this subject, but the degree of depth to which these topics are covered varies.

Career development isn’t introduced until the section on emerging adulthood. Research dating back 50+ years discusses career development in the context of childhood and adolescence. Not including career development is a disservice to the career development programming that has been done and continues to be done in K-12 settings.

The textbook covers many of the theories of human development, but does not introduce all of them in the first chapter. Only a select few are covered in this introduction; other theories are introduced in later chapters in the point in the lifespan during which this theory becomes most salient. This is problematic, as the stages are not firmly restricted to these age bands. A review of all theories in the beginning would be helpful to the reader. The book does not cover some theories (e.g., Spiritual development).

Adverse childhood experiences (ACEs) are not covered at all, and the research has been around for 20 years. Any discussion of human development that does not include this research is incomplete.

Other topics (e.g., sexuality, gender identity) are presented in greater detail than other texts I’ve seen. The discussion of grief models, especially refutations of the Kubler-Ross model, are excellent and represent modern research.

The information presented in the text appears to be accurate, with the exception of a few areas that need to be updated with contemporary research.

The text does not include contemporary research on Adverse Childhood Experiences, neuroimaging, and neuropsychology. This contemporary research has enhanced or refuted many long-held theories and must be represented in any discussion of human development

The information presented is written clearly and in a way that is easy to understand and comprehend.

The book appears to be presented in a consistent manner, with regard to terminology, framework, and layout. The authors were not consistent with the depth to which topics are covered; this may be an indication of the authors areas of interest and areas for development.

The book is chunked very well. The chapters are broken down in a rational manner and each chapter includes many smaller sections with headings.

The book is chunked very well. The chapters are broken down in a rational manner and each chapter includes many smaller sections with headings. The authors were not consistent with the depth to which topics are covered; this may be an indication of the authors areas of interest and areas for development.

The book has a very good look. The table of contents is navigable, and there are links to sources embedded within. The graphics, tables, and charts are clear and readable.

The authors use correct grammar and have edited the book well for mechanical and grammatical errors.

The book presents cultural information more completely in some areas and more incompletely in other areas. This is an area of the text that could use additional fine-tuning. Stereotype threat introduced in the section on age, although the research emerged from discussions of race and ethnicity. The book covers sexuality and gender identity in more depth than other texts I’ve used.

Based on the current edition of the text, I cannot say that I would use this book over a traditionally published text without having to provide many additional readings to supplement incomplete areas. At best, there are chapters from this text I could see assigning to supplement additional readings.

Chapter 1: Introduction to Lifespan Development
Chapter 2: Heredity, Prenatal Development, and Birth
Chapter 3: Infancy and Toddlerhood
Chapter 4: Early Childhood
Chapter 5: Middle and Late Childhood
Chapter 6: Adolescence
Chapter 7: Emerging and Established Adulthood
Chapter 8: Middle Adulthood
Chapter 9: Late Adulthood
Chapter 10: Death and Dying

Ancillary Material

About the book.

Developmental Psychology, also known as Human Development or Lifespan Development, is the scientific study of ways in which people change, as well as stay the same, from conception to death. You will no doubt discover in the course of studying that the field examines change across a broad range of topics. These include physical and other psychophysiological processes, cognition, language, and psychosocial development, including the impact of family and peers.

About the Contributors

Martha Lally is an Instructor in the Psychology department at the College of Lake County.

Suzanne Valentine-French is an Instructor in the Psychology department at the College of Lake County.

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Overview of the Scientific Method

Learning Objectives

Distinguish between a theory and a hypothesis.
Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers begin with a set of phenomena and either construct a theory to explain or interpret them or choose an existing theory to work with. They then make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary. This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 2.3 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [3] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans [Zajonc & Sales, 1966] [4] in many other studies afterward).

Incorporating Theory into Your Research

Characteristics of a Good Hypothesis

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that it really does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

Zajonc, R. B. (1965). Social facilitation. Science, 149 , 269–274 ↵
Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

A coherent explanation or interpretation of one or more phenomena.

A specific prediction about a new phenomenon that should be observed if a particular theory is accurate.

The ability to test the hypothesis using the methods of science and the possibility to gather evidence that will disconfirm the hypothesis if it is indeed false.

Research Methods in Psychology Copyright © 2019 by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Concepts and Categories: A Cognitive Neuropsychological Perspective

Bradford z. mahon.

1 Department of Psychology, Harvard University, Cambridge, Massachusetts 02318

2 Center for Mind/Brain Sciences, CIMeC, University of Trento, Rovereto (TN), Italy 38068

Alfonso Caramazza

One of the most provocative and exciting issues in cognitive science is how neural specificity for semantic categories of common objects arises in the functional architecture of the brain. More than two decades of research on the neuropsychological phenomenon of category-specific semantic deficits has generated detailed claims about the organization and representation of conceptual knowledge. More recently, researchers have sought to test hypotheses developed on the basis of neuropsychological evidence with functional imaging. From those two fields, the empirical generalization emerges that object domain and sensory modality jointly constrain the organization of knowledge in the brain. At the same time, research within the embodied cognition framework has highlighted the need to articulate how information is communicated between the sensory and motor systems, and processes that represent and generalize abstract information. Those developments point toward a new approach for understanding category specificity in terms of the coordinated influences of diverse regions and cognitive systems.

INTRODUCTION

The scientific study of how concepts are represented in the mind/brain extends to all disciplines within cognitive science. Within the psychological and brain sciences, research has focused on studying how the perceptual, motor, and conceptual attributes of common objects are represented and organized in the brain. Theories of conceptual representation must therefore explain not only how conceptual content itself is represented and organized, but also the role played by conceptual content in orchestrating perceptual and motor processes.

Cognitive neuropsychological studies of brain-damaged patients provide strong evidence about the representation of conceptual knowledge and the relationship between conceptual knowledge and perceptual and motor processes. The cognitive neuropsychological approach ultimately seeks to evaluate models of cognitive processing through the proximate goal of explaining the profile of behavioral performance observed in brain-damaged patients. In the measure to which it is possible to establish the functional locus of impairment in a patient within a given model of cognitive functioning, then it is possible to test other assumptions of that model through further experiments with that patient. Dissociations of abilities in patients (and of processes in models) are central to the neuropsychological approach. This is because if a given behavior/process X can be impaired while another behavior/process Y is preserved, then one may conclude that the former process is not causally involved in the latter process. Another important source of evidence from neuropsychology are aspects of cognitive functioning that are observed to be systematically impaired or spared together (for discussion of methodological issues in cognitive neuropsychology, see Caramazza 1986 , 1992 ; Shallice 1988 ).

Scope of the Review

The modern study of the representation of concepts in the brain was initiated by a series of papers by Elizabeth Warrington, Tim Shallice, and Rosaleen McCarthy. Those authors described patients with disproportionate semantic impairments for one, or several, categories of objects compared to other categories (see Hécaen & De Ajuriaguerra 1956 for earlier work). Since those initial investigations, a great deal has been learned about the causes of category-specific semantic deficits, and by extension, the organization of object knowledge in the brain.

The focus of this review is on neuropsychological research, and in particular, on the phenomenon of category-specific semantic deficits. Evidence from other fields within cognitive science and neuroscience and functional neuroimaging is reviewed as it bears on the theoretical positions that emerge from the study of category-specific semantic deficits. In particular, we highlight findings in functional neuroimaging related to the representation of different semantic categories in the brain. We also discuss the degree to which conceptual representations are grounded in sensory and motor processes, and the critical role that neuropsychological studies of patients with impairments to sensory and motor knowledge can play in constraining theories of semantic representation.

CATEGORY-SPECIFIC SEMANTIC DEFICITS: INTRODUCTION TO THE PHENOMENON

Patients with category-specific semantic deficits present with disproportionate or even selective impairments for one semantic category compared to other semantic categories. Figure 1 illustrates cases of disproportionate impairment for animals ( upper left ; Blundo et al. 2006 , Caramazza & Shelton 1998 ), fruit/vegetables ( upper right ; Hart et al. 1985 , Samson & Pillon 2003 ), conspecifics ( lower left ; Miceli et al. 2000 , Ellis et al. 1989 ), and non-living things ( lower right ; Laiacona & Capitani 2001 , Sacchett & Humphreys 1992 ). More than one hundred cases of category-specific semantic impairment have been reported (for review and discussion, see Capitani et al. 2003 , Hart et al. 2007 , Humphreys & Forde 2001 , Tyler & Moss 2001 ). The majority of reported patients have disproportionate impairments for living things compared to nonliving things ( Capitani et al. 2003 ).

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Representative picture naming performance of patients with category-specific semantic deficits for ( a ) living animate things, ( b ) fruit/vegetables, ( c ) conspecifics, and ( d ) nonliving.

One important aspect of the performance profile of patients with category-specific semantic impairment is that the impairment is to conceptual knowledge and not (only) to modality-specific input or output representations. The evidence for locating the deficit at a conceptual level is that the category-specific deficit does not depend on stimuli being presented or that patients respond in only one modality of input or output. For instance, patients KC and EW ( Figure 1 a ) were impaired for naming living animate things compared to nonliving things and fruit/vegetables. Both patients were also impaired for answering questions about living animate things, such as “Does a whale have legs” or “Are dogs domestic animals,” but were unimpaired for the same types of questions about nonanimals ( Figure 2 a , for data from EW and other representative patients).

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Relation between impairments for a type or modality of knowledge and category-specific semantic deficits. These data show that ( a ) category-specific semantic impairments are associated with impairments for all types of knowledge about the impaired category, ( b ) differential impairments for visual/perceptual knowledge can be associated with (if anything) a disproportionate impairment for nonliving things compared to living things, and ( c ) selective impairment for knowledge of object color is not associated with a corresponding disproportionate deficit for fruit/vegetables. Data for EW from Caramazza & Shelton 1998 ; GR and FM from Laiacona et al. 1993 ; DB from Lambon Ralph et al. 1998 ; and RC from Moss et al. 1998 .

Patients with category-specific semantic deficits may have additional, and also category-specific, deficits at presemantic levels of processing. For instance, patient EW was impaired for judging whether pictures depicted real or unreal animals but was unimpaired for the same task over nonanimal stimuli. The ability to make such decisions is assumed to index the integrity of the visual structural description system, a presemantic stage of object recognition ( Humphreys et al. 1988 ). In contrast, patient KC was relatively unimpaired on an object decision task, even for the category of items (living animate) that the patient was unable to name. A similar pattern to that observed in patient KC was present in patient APA ( Miceli et al. 2000 ). Patient APA was selectively impaired for conceptual knowledge of people (see Figure 1 c ). Despite a severe impairment for naming famous people, APA did not have a deficit at the level of face recognition (prosopagnosia).

Another important aspect of patients with category-specific semantic impairments is that they have difficulty distinguishing among basic-level items within the impaired category but do not necessarily have problems assigning items they cannot identify to the correct superordinate level category (e.g., they may know that a picture of a dog is an animal, but do not know which animal) (see Humphreys & Forde 2005 for discussion of a patient with greater difficulty at a superordinate than a basic level across all semantic categories).

A number of studies have now documented that variables such as lexical frequency, concept familiarity, and visual complexity may be unbalanced if items are sampled randomly from different semantic categories ( Cree & McRae 2003 , Funnell & Sheridan 1992 , Stewart et al. 1992 ). In addition, Laiacona and colleagues ( Barbarotto et al. 2002 , Laiacona et al. 1998 ) have highlighted the need to control for gender-specific effects on variables such as concept familiarity (for discussion of differences between males and females in the incidence of category-specific semantic deficits for different categories, see Laiacona et al. 2006 ). However, the existence of category-specific semantic deficits is not an artifact of such stimulus-specific attributes. Clear cases have been reported for which stimulus-specific variables have been carefully controlled, and double dissociations have been reported using the same materials (e.g., Hillis & Caramazza 1991 ; see also the separate case reports in Barbarotto et al. 1995 and Laiacona & Capitani 2001 ).

OVERVIEW OF THEORETICAL EXPLANATIONS OF THE CAUSES OF CATEGORY-SPECIFIC SEMANTIC DEFICITS

Theories developed in order to explain category-specific semantic deficits fall into two broad groups ( Caramazza 1998 ). Theories within the first group, based on the neural structure principle, assume dissociable neural substrates are differentially (or exclusively) involved in representing different semantic categories. Theories within the second group, based on the correlated structure principle, assume that conceptual knowledge of items from different semantic categories is not represented in functionally dissociable regions of the brain.

According to theories based on the neural structure principle, category-specific semantic deficits are due to differential or selective damage to the neural substrate upon which the impaired category of items depends. Two broad classes of theories based on the neural structure principle are the sensory/functional theory ( Warrington & McCarthy 1983 , 1987 ; Warrington & Shallice 1984 ) and the domain-specific hypothesis ( Caramazza & Shelton 1998 ).

The sensory/functional theory is composed of two assumptions. The first—the multiple semantics assumption—is that conceptual knowledge is organized into subsystems that parallel the sensory and motor modalities of input and output. The second assumption is that the critical semantic attributes of items from different categories of objects are represented in different modality-specific semantic subsystems.

The domain-specific hypothesis assumes that the first-order constraint on the organization of conceptual knowledge is object domain, with the possible domains restricted to those that could have had an evolutionarily relevant history—living animate, living inanimate, con-specifics, and tools.

Theories based on the correlated structure principle model semantic memory as a system that represents statistical regularities in the co-occurrence of object properties in the world ( Caramazza et al. 1990 , Devlin et al. 1998 , McClelland & Rogers 2003 , Tyler & Moss 2001 ). This class of models has been instrumental in motivating large-scale empirical investigations of how different types of features are distributed and correlated for different semantic categories. Several theories based on the correlated structure principle have been developed in order to explain the causes of category-specific semantic deficits ( Caramazza et al. 1990 , Devlin et al. 1998 , Tyler & Moss 2001 ).

This review is organized to reflect the role that different theoretical assumptions have played in motivating empirical research. Initial hypotheses that were developed in order to explain category-specific semantic deficits appealed to a single principle of organization (modality specificity, domain specificity, or correlated structure). The current state of the field of category-specific semantic deficits is characterized by complex models that integrate assumptions from multiple theoretical frameworks (for discussion, see Caramazza & Mahon 2003 ).

THE NEURAL STRUCTURE PRINCIPLE

The multiple semantics assumption.

Beauvois initially proposed that the organization of the semantic system follows the organization of the various input and output modalities to and from the semantic system ( Beauvois 1982 , Beauvois et al. 1978 ). The original motivation for the assumption of multiple semantics was the phenomenon of optic aphasia (e.g., Lhermitte & Beavuois 1973 ; for review, see Plaut 2002 ). Patients with optic aphasia present with impaired naming of visually presented objects but relatively (or completely) spared naming of the same objects when presented through the tactile modality (e.g., Hillis & Caramazza 1995 ). The fact that optic aphasic patients can name objects presented through the tactile modality indicates that the naming impairment to visual presentation is not due to a deficit at the level of retrieving the correct names. In contrast to patients with visual agnosia (e.g., Milner et al. 1991 ), patients with optic aphasia can recognize, at a visual level of processing, the stimuli they cannot name. Evidence for this is provided by the fact that some optic aphasic patients can demonstrate the correct use of objects that they cannot name (e.g., Coslett & Saffran 1992 , Lhermitte & Beauvois 1973 ; for discussion, see Plaut 2002 ). Beauvois (1982) explained the performance of optic aphasic patients by assuming that the conceptual system is functionally organized into visual and verbal semantics and that optic aphasia is due to a disconnection between the two semantic systems.

Along with reporting the first cases of category-specific semantic deficit, Warrington and her collaborators ( Warrington & McCarthy 1983 , Warrington & Shallice 1984 ) developed an influential explanation of the phenomenon that built on the proposal of Beauvois (1982) . Warrington and colleagues argued that category-specific semantic deficits are due to differential damage to a modality-specific semantic subsystem that is not itself organized by semantic category. Specifically, those authors noted that the patients they had reported with impairments for living things also had impairments for foods, plants, and precious stones ( Warrington & Shallice 1984 ); in contrast, a patient with an impairment for nonliving things ( Warrington & McCarthy 1983 ) was spared for living things, food, and plant life. Warrington and her collaborators reasoned that the association of impaired and spared categories was meaningfully related to the degree to which identification of items from those categories depends on sensory or functional knowledge. Specifically, they argued that the ability to identify living things differentially depends on sensory knowledge, whereas the ability to identify nonliving things differentially depends on functional knowledge.

Farah & McClelland (1991) implemented the theory of Warrington and colleagues in a connectionist framework. Three predictions follow from the computational model of Farah & McClelland (1991 ; for discussion, see Caramazza & Shelton 1998 ). All three of those predictions have now been tested. The first prediction is that the grain of category-specific semantic deficits should not be finer than living versus nonliving. This prediction follows from the assumption that all living things differentially depend on visual knowledge. However, as represented in Figure 1 , patients have been reported with selective semantic impairments for fruit/vegetables (e.g., Hart et al. 1985 , Laiacona et al. 2005 , Samson & Pillon 2003 ) and animals (e.g., Blundo et al. 2006 , Caramazza & Shelton 1998 ). The second prediction is that an impairment for a given category of knowledge will be associated with a disproportionate impairment for the modality of knowledge that is critical for that category. At variance with this prediction, it is now known that category-specific semantic deficits are associated with impairments for all types of knowledge (sensory and functional) about items from the impaired category ( Figure 2 a ; e.g., Blundo et al. 2006 , Caramazza & Shelton 1998 , Laiacona & Capitani 2001 , Laiacona et al. 1993 , Lambon Ralph et al. 1998 , Moss et al. 1998 ). The third prediction is that impairments for a type of knowledge will necessarily be associated with differential impairments for the category that depends on that knowledge type. Patients exhibiting patterns of impairment contrary to this prediction have been reported. For instance, Figure 2 b shows the profile of a patient who was ( a ) more impaired for visual compared to functional knowledge, and ( b ) if anything, more impaired for nonliving things than living things ( Lambon Ralph et al. 1998 ; see also Figure 2 c , Figure 4 , and discussion below).

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Relation between knowledge of how to manipulate tools and other knowledge of tools. ( a ) Ochipa and colleagues (1989) reported a patient with a severe impairment for manipulating objects but relatively preserved naming of the same objects. ( b ) A multiple single-case study of unselected unilateral stroke patients asked patients to use and identify the same set of objects ( Negri et al. 2007 ). Performance of the patients is plotted as t values ( Crawford & Garthwaite 2006 ) compared to control (n = 25) performance. ( c ) Lesions to parietal cortex, in the context of lesions to lateral temporal and frontal regions, can be instrumental in modulating the relationship between performance in object identification and object use, at the group level (see Mahon et al. 2007 , figure 7, for details and lesion overlap analyses). Each circle in the plots represents the performance of a single patient in object identification and object use. The 95% confidence intervals around the regression lines are shown. Reproduced with permission from Mahon and colleagues (2007) . ( d ) Patient WC ( Buxbaum et al. 2000 ) was impaired for matching pictures based on how objects are manipulated but was spared for matching pictures based on the function of the objects.

Second Generation Sensory/Functional Theories

The original formulation of the sensory/functional theory was based on a simple division between visual/perceptual knowledge and functional/associative knowledge. Warrington & McCarthy (1987 ; see also Crutch & Warrington 2003 ) suggested, however, that knowledge of object color is differentially important for fruit/vegetables compared to animals. Since Warrington and McCarthy’s proposal, further sensory- and motor-based dimensions that may be important for distinguishing between semantic categories have been articulated (e.g., Cree & McRae 2003 , Vinson et al. 2003 ).

Cree & McRae (2003) used a feature-listing task to study the types of information that normal subjects spontaneously associate with different semantic categories. The semantic features were then classified into nine knowledge types: color, visual parts and surface properties, visual motion, smell, sound, tactile, taste, function, and encyclopedic (see Vinson et al. 2003 for a slightly different classification). Hierarchical cluster analyses were used to determine which semantic categories differentially loaded on which feature types. The results of those analyses indicated that ( a ) visual motion and function information were the two most important knowledge types for distinguishing living animate things (high on visual motion information) from nonliving things (high on function information), ( b ) living animate things were weighted lower on color information than fruit/vegetables, but higher on this knowledge type than nonliving things, and ( c ) fruit/vegetables were distinguished from living animate and nonliving things by being weighted the highest on both color and taste information.

Cree and McRae’s analyses support the claim that the taxonomy of nine knowledge types is effective in distinguishing between the domains living animate, fruit/vegetables, and nonliving. Those analyses do not demonstrate, however, that the nine knowledge types are critical for distinguishing between items within the respective categories. As noted above, patients with category-specific semantic impairments do not necessarily have difficulty distinguishing between different domains (i.e., they might know it is an animal but cannot say which one). It is therefore not obvious that Cree and McRae’s analyses support the claim that category-specific semantic deficits may be explained by assuming damage to one (or more) of the nine knowledge types.

At a more general level, the open empirical question is whether the additional knowledge types and the corresponding further functional divisions that are introduced into the semantic system can account for the neuropsychological evidence. Clearly, if fruit/vegetables and animals are assumed to differentially depend on different types of information (and by inference, different semantic subsystems), it is in principle possible to account for the tripartite distinction between animals, fruit/vegetables, and nonliving. As for the original formulation of the sensory/functional theory, the question is whether fine-grained category-specific semantic impairments are associated with impairments for the type of knowledge upon which items from the impaired category putatively depend. However, patients have been reported with category-specific semantic impairments for fruit/vegetables, without disproportionate impairments for color knowledge (e.g., Samson & Pillon 2003 ). Patients have also been reported with impairment for knowledge of object color without a disproportionate impairment for fruit/vegetables compared to other categories of objects (see Figure 2c ; Luzzatti & Davidoff 1994 , Miceli et al. 2001 ).

Another way in which investigators have sought to provide support for the sensory/functional theory is to study the semantic categories that are systematically impaired together. As noted above, one profile of the first reported cases that motivated the development of the sensory/functional theory ( Warrington & Shallice 1984 ) was that the categories of animals, plants, and foods tended to be impaired or spared together. Those associations of impairing and sparing of categories made sense if all of those categories depended on the same modality-specific system for their identification. Following the same logic, it was argued that musical instruments patterned with living things (because of the importance of sensory attributes) (see Dixon et al. 2000 for relevant data), and that body parts patterned with nonliving things (because of the importance of functional attributes associated with object usage (e.g., Warrington & McCarthy 1987 ). However, as was the case for the dissociation between living animate things (animals) and living inanimate things (e.g., plants), it is now known that musical instruments dissociate from living things and that body parts dissociate from nonliving things ( Caramazza & Shelton 1998 , Laiacona & Capitani 2001 , Shelton et al. 1998 , Silveri et al. 1997 , Turnbull & Laws 2000 ; for review and discussion, see Capitani et al. 2003 ).

More recently, Borgo & Shallice (2001 , 2003) have argued that sensory-quality categories, such as materials, edible substances, and drinks are similar to animals in that they depend on sensory information for their identification. Those authors reported that impairment for living things was associated with impairments for sensory-quality categories. However, Laiacona and colleagues (2003) reported a patient who was impaired for living things but spared for sensory-quality categories (for further discussion, see Carroll & Garrard 2005 ).

Another dimension that has been argued to be instrumental in accounting for category-specific semantic deficits is differential similarity in the visual structure of items from different categories. Humphreys & Forde (2001 ; see also Tranel et al. 1997 ) argued that living things tend to be more structurally similar than nonliving things. If that were the case, then it could be argued that damage to a system not organized by object category will result in disproportionate disruption of items that are more “confusable” (see also Lambon Ralph et al. 2007 , Rogers et al. 2004 ). Within Humphreys and Forde’s framework, it is also assumed that activation dynamically cascades from visual object recognition processes through to lexical access. Thus, perturbation of visual recognition processes could trickle through the system to disrupt the normal functioning of subsequent processes, resulting in a naming deficit (see Humphreys et al. 1988 ). Laws and colleagues ( Laws & Gale 2002 , Laws & Neve 1999 ) also argued for the critical role of similarity in visual structure for explaining category-specific semantic deficits. However, in contrast to Humphreys and Forde (see also Tranel et al. 1997 ), Laws and colleagues argued that nonliving things tend to be more similar than living things.

Clearly, much work remains to be done in order to understand the role that visual similarity, and the consequent crowding ( Humphreys & Forde 2001 ) of visual representations, has in explaining category-specific semantic deficits. On the one hand, there is no consensus regarding the relevant object properties over which similarity should be calculated or how such a similarity metric should be calculated. On the other hand, assuming an agreed-upon means for determining similarity in visual shape, the question remains open as to the role that such a factor might play in explaining the facts of category-specific semantic deficits.

The Domain-Specific Hypothesis

The domain-specific hypothesis of the organization of conceptual knowledge in the brain ( Caramazza & Shelton 1998 ) assumes that the first-order constraint on the organization of information within the conceptual system is object domain. The semantic categories that may be organized by domain-specific constraints are limited to those that could have had an evolu-tionarily relevant history: living animate, living inanimate, conspecifics, and tools. On this proposal, the phenomenon of category-specific semantic deficit reflects differential or selective damage to the neural substrates that support one or another domain of knowledge. Research from developmental psychology converges with the assumption that conceptual knowledge is organized, in part, by innately specified constraints on object knowledge (e.g., Baillargeon 1998 , Carey & Spelke 1994 , Gallistel 1990 , Gelman 1990 , Keil 1981 , Spelke et al. 1992 , Wellman & Gelman 1992 ; for a review, see Santos & Caramazza 2002 ; see, e.g., Kiani et al. 2007 for convergent findings using neurophysiological methods with nonhuman primates). Research in developmental psychology has also highlighted other domains of knowledge beyond those motivated by neuropsychological research on patients with category-specific deficits, such as number and geometric/spatial reasoning (e.g., JF Cantlon, M Platt, & EM Brannon, manuscript under review ; Feigenson et al. 2004 ; Hermer & Spelke 1994 ).

Unique predictions are generated by the original formulation of the domain-specific hypothesis as it was articulated in the context of category-specific semantic deficits. One prediction is that the grain of category-specific semantic deficits will reflect the grain of those categories that could plausibly have had an evolutionarily relevant history (see Figure 1 ). Another prediction is that category-specific semantic impairments will be associated with impairments for all types of knowledge about the impaired category (see Figure 2a ). A third prediction made by the domain-specific hypothesis is that it should be possible to observe category-specific impairments that result from early damage to the brain. Evidence in line with this expectation is provided by the case of Adam ( Farah & Rabinowitz 2003 ). Patient Adam, who was 16 at the time of testing, suffered a stroke at one day of age. Adam failed to acquire knowledge of living things, despite normal levels of knowledge about nonliving things. As would be expected within the framework of the domain-specific hypothesis, Adam was impaired for both visual and nonvisual knowledge of living things ( Farah & Rabinowitz 2003 ).

The Distributed Domain-Specific Hypothesis

The original formulation of the domain-specific hypothesis ( Caramazza & Shelton 1998 ) anticipated the possibility of other dimensions of organization beyond object domain. It was proposed that correlational structure plays an important role in determining the organization of knowledge within domains. More important in the present context, it was also proposed that domain specificity would be found at both conceptual and perceptual levels of processing. We have since attempted to develop this account and have explored a model in which ( a ) object domain and sensory, motor, and emotional properties jointly constrain the organization of conceptual knowledge, and ( b ) object domain is a constraint on the organization of information at both a conceptual level as well as at the level of modality-specific visual input representations ( Caramazza & Mahon 2003 , 2006 ; Mahon & Caramazza 2003 , 2008 ). We refer to this framework as the distributed domain-specific hypothesis in order to capture the idea that both object domain and a distributed network of modality-specific representations constrain the organization of conceptual knowledge of objects (we previously referred to this view as the domain-specific sensory-motor hypothesis; Mahon & Caramazza 2008 ). The central idea of this proposal is that domain-specific organization within a particular region is driven, in part, by the functional connectivity of the brain. That is, domain specificity is determined not only by the specific characteristics of processing within a given region, but also by how information in that region relates to information that is computed elsewhere and which is salient for the domain. The grain of that functional connectivity, according to the hypothesis, should reflect those object domains with evolutionarily important histories.

One expectation on the distributed domain-specific hypothesis is that impairments to abstract conceptual knowledge will dissociate from category-specific impairments at the level of object recognition. Consistent with this, and as noted above, impairments to conceptual knowledge are not necessarily associated with impairments at a modality-specific input level of visual processing. Some patients with conceptual-level impairments do have associated impairments for recognizing visually presented items (e.g., Caramazza & Shelton 1998 ), whereas other patients do not (e.g., Blundo et al. 2006 ; for a review, see Capitani et al. 2003 ).

Further convergent evidence is provided by the study of prosopagnosia. Patients with prosopagnosia have a deficit for recognizing visually presented faces but do not have difficulties retrieving other knowledge about the people they cannot recognize. For instance, such patients may be able to recognize the same people by the sound of their voice. The reverse dissociation—sparing of face recognition compared to recognition of other categories—has also been reported ( Moscovitch et al. 1997 ).

Patients with prosopagnosia also constitute the other side of a double dissociation with patients such as APA, discussed above (see Figure 1c ; Miceli et al. 2000 ). Patients such as APA are impaired for conceptual knowledge of conspecifics but are not necessarily prosopagnosic. Thus, within the domain of conspecifics, category-specific deficits at a modality-specific level of visual recognition dissociate from impairments to more abstract knowledge of conspecifics. In addition, prosopagnosia can arise developmentally, suggesting that the constraints that drive neural specificity for face perception are, in part, innately specified ( Duchaine et al. 2006 , Nunn et al. 2001 ; for a comprehensive review of acquired and developmental prosopagnosia, see Duchaine & Yovel 2008 ).

THE CORRELATED STRUCTURE PRINCIPLE

Theories based on the correlated structure principle assume that the conceptual system has no structure that is specifically reflected in functional neuroanatomy. For instance, the organized unitary content hypothesis (OUCH) ( Caramazza et al. 1990 ) was initially formulated as an explanation of optic aphasia that did not invoke the assumption of multiple semantics. Caramazza and colleagues (1990 ; see also Riddoch et al. 1988 ) argued that there are privileged relationships between certain types of input representations (e.g., visual form) and certain types of output representations (e.g., knowledge of object manipulation), thus explaining how optic aphasic patients might be spared for gesturing to objects while impaired for naming them.

Other researchers subsequently developed highly specified proposals based on the correlated structure principle, all of which build on the idea that different types of features are differentially correlated across different semantic categories ( Devlin et al. 1998 , Rogers et al. 2004 , Tyler & Moss 2001 ). Those models of semantic memory have been implemented computationally, with simulated damage, in order to provide existence proofs that a system with no explicit functional organization may be damaged so as to produce category-specific semantic deficits. Because theories based on the correlated structure principle do not assume that the conceptual system has structure at the level of functional neuroanatomy, they are best suited to modeling the patterns of progressive loss of conceptual knowledge observed in neurodegenerative diseases, such as dementia of the Alzheimer type and semantic dementia. The type of damage in such patients is diffuse and widespread and can be modeled in connectionist architectures by removing, to varying degrees, randomly selected components of the network.

One important proposal is the conceptual-structure account of Tyler, Moss, and colleagues ( Bright et al. 2005 , Tyler & Moss 2001 ). That proposal assumes that living things have more shared features, whereas nonliving things have more distinctive features. The model further assumes that the shared features of living things are highly correlated (has eyes/can see), whereas for nonliving things, distinctive features are highly correlated (used for spearing/has tines). If distinctive features are critical for identification, and if greater correlation confers resilience to damage, then an interaction between the severity of overall impairment and the direction of category-specific semantic deficit is predicted. Mild levels of impairments should produce disproportionate impairments for living things compared to nonliving things. At more severe levels of impairments, the distinctive features of nonliving things will be lost and a disproportionate impairment for this category will be observed. The opposite prediction regarding the severity of overall impairment and the direction of category-specific impairment is predicted by the account of Devlin and colleagues (1998) because it is assumed that as damage becomes severe, whole sets of intercorrelated features will be lost, resulting in a disproportionate impairment for living things. However, it is now known that neither prediction finds clear empirical support ( Garrard et al. 1998 , Zannino et al. 2002 ; see also Laiacona & Capitani 2001 for discussion within the context of focal lesions; for further discussion and theoretical developments, see Cree & McRae 2003 , Vinson et al. 2003 ).

One issue that is not resolved is whether correlations between different features should be calculated in a concept-dependent or concept-independent manner ( Zannino et al. 2006 ). For instance, although the (distinctive) information “has tines” is highly correlated with the function “used for spearing” in the concept FORK (correlated as concept dependent), the co-occurrence of those properties in the world is relatively low (concept independent). Sartori, Lombardi, and colleagues ( Sartori & Lombardi 2004 , Sartori et al. 2005 ) have addressed a similar issue by developing the construct of “semantic relevance,” which is computed through a nonlinear combination of the frequency with which particular features are produced for an item and the distinctiveness of that feature for all concepts in the database. Those authors have shown that living things tend to be lower, on average, than nonliving things in terms of their relevance, thus making living things on average “harder” than nonliving things. As is the case for other accounts of category-specific semantic deficits that are based on differences across categories along a single dimension, the existence of disproportionate deficits for the relatively “easy” category (nonliving things) is difficult to accommodate (see e.g., Hillis & Caramazza 1991 , Laiacona & Capitani 2001 ; Figure 1 d ). Nevertheless, the theoretical proposal of Sartori and colleagues highlights the critical and unresolved issue of how to determine the psychologically relevant metric for determining feature correlations.

Another unresolved issue is whether high correlations between features will provide resilience to damage for those features, or will rather make damage contagious among them. It is often assumed that high correlation confers resilience to, or insulation from, damage; however, our understanding of how damage to one part of the brain affects other regions of the brain remains poorly developed. It is also not obvious that understanding the behavior of connectionist architectures constitutes the needed motivation for deciding whether greater correlation confers greater resilience to damage. In fact, theoretical differences about the role of correlations in conferring resilience to damage are in part responsible for the contrasting predictions that follow from the models of Tyler and colleagues ( Tyler & Moss 2001 ) and Devlin and colleagues (1998) (for discussion, see Zannino et al. 2006 ).

Another example that illustrates our current lack of understanding of the role of feature correlation in determining patterns of impairment is provided by dissociations between sensory, motor, and conceptual knowledge. For instance, the visual structure of objects is highly correlated with more abstract knowledge of the conceptual features of objects. Even so, patients with impairments to abstract conceptual features of objects do not necessarily have corresponding impairments to object recognition processes (see above and Capitani et al. 2003 for review). Similarly, although manipulation knowledge (“how to” knowledge) is correlated with functional knowledge (“what for” knowledge), damage to the former does not imply damage to the latter (see Buxbaum et al. 2000 , Figure 4 d , and discussion below).

Theories based on the correlated structure principle are presented as alternatives to proposals that assume neural structure within the conceptual system. The implicit assumption in that argument is that the theoretical construct of a semantic feature offers a means for reducing different categories to a common set of elements (see Rogers et al. 2004 for an alternative proposal). However, no semantic features have been described that are shared across semantic categories, aside from very abstract features such as “has mass.” In other words, in the measure to which semantic features are the substance of conceptual representations, different semantic categories would be represented by nonoverlapping sets of features. Thus, and as has been proposed on the basis of functional neuroimaging data (see, e.g., Haxby et al. 2001 and discussion below), it may be the case that regions of high feature correlation (e.g., within semantic category correlations in visual structure) are reflected in the functional neuroanatomy of the brain (see also Devlin et al. 1998 for a hybrid model in which both focal and diffuse lesions can produce category-specific effects and Caramazza et al. 1990 for an earlier proposal along those lines).

THE ANATOMY OF CATEGORY-SPECIFICITY

An important development in cognitive neuroscience that has paralleled the articulation of theories of semantic organization is the discovery of multiple channels of visual processing ( Goodale & Milner 1992 , Ungerleider & Miskin 1982 ). It is now known that visual processing bifurcates into two independent but interconnected streams (for discussion of how best to characterize the two streams, see Pisella et al. 2006 ). The ventral visual object–processing stream projects from V1 through ventral occipital and temporal cortices, terminating in anterior regions of the temporal lobe, and subserves visual object identification. The dorsal object–processing stream projects from V1 through dorsal occipital cortex to posterior parietal cortex and subserves object-directed action and spatial analysis for the purposes of object-directed grasping. The two-visual systems hypothesis has played a central role in understanding the neuroanatomy of category specificity.

Lesion Analyses

A natural issue to arise in neuropsychological research concerns which brain regions tend to be lesioned in association with category-specific deficits. The first study to address this issue systematically was by H. Damasio and colleagues (1996) . Those authors found that name-retrieval deficits for pictures of famous people were associated with left temporal pole lesions, a result confirmed by other investigators (see Lyons et al. 2006 for an overview). Damasio and colleagues also found that deficits for naming animals were associated with (more posterior) lesions of anterior left ventral temporal cortex. Subsequent research has confirmed that deficits for naming animals are associated with lesions to anterior regions of temporal cortex (e.g., Brambati et al. 2006 ). Damasio and collaborators also found that deficits for naming tools were associated with lesions to posterior and lateral temporal areas, overlapping the left posterior middle gyrus. The critical role of the left posterior middle temporal gyrus for knowing about tools has also since been confirmed by other lesion studies (e.g., Brambati et al. 2006 ).

A subsequent report by Damasio and colleagues (2004) demonstrated that the same regions were also reliably damaged in patients with impairments for recognizing stimuli from those three categories. In addition, Damasio and colleagues (2004) found that deficits for naming tools, as well as fruit/vegetables, were associated with lesions to the inferior pre-and postcentral gyri as well as the insula. Consensus about the association of lesions to the regions discussed above with category-specific deficits is provided by Gainotti’s analyses (e.g., Gainotti 2000 ) of published reports of patients with category-specific semantic deficits.

A number of investigators have interpreted the differential role of anterior mesial aspects of ventral temporal cortex in the processing of living things to reflect the fact that living things have more shared properties than non-living things, such that more fine-grained discriminations are required to name them ( Bright et al. 2005 , Damasio et al. 2004 , Simmons & Barsalou 2003 ; see also Humphreys & Forde 2001 ). Within this framework, the association of deficits to unique person knowledge and lesions to the most anterior aspects of the temporal lobe is assumed to reflect the greater discrimination that is required for distinguishing among conspecifics compared to animals (less) and nonliving things (even less).

Functional Imaging

Data from functional imaging, and in particular fMRI, have added in important ways to our understanding of how different semantic categories are processed in the healthy brain. In particular, although the lesion overlap approach is powerful in detecting brain regions that are critical for performing a given task, functional imaging has the advantage of detecting regions that are critical as well as regions that are automatically engaged by the mere presentation of a certain type of stimulus. Thus, in line with the lesion evidence described above, nonliving things, and in particular tools, differentially activate the left middle temporal gyrus ( Figure 3 , e.g., Martin et al. 1996 , Thompson-Schill et al. 1999 ; see Devlin et al. 2002 for a review). Other imaging data indicate that this region plays an important role in processing the semantics of actions (e.g., Kable et al. 2002 , Kemmerer et al. 2008 , Martin et al. 1995 ) as well as mechanical (i.e., unarticulated) motion ( Beauchamp et al. 2002 , 2003 ; Martin & Weisberg 2003 ).

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Category-specific patterns of blood oxygen–level dependent (BOLD) responses in the healthy brain. A network of regions that are differentially activated for living animate things is in red; a network of regions that are differentially activated for nonliving things is in blue. Data from Chao et al. (2002) ; graphics provided by Alex Martin.

In contrast, and not as apparent in lesion studies, tools differentially activate dorsal stream regions that mediate object-directed action. The activation of some of those regions is independent of whether action information is necessary in order to perform the task in which participants are engaged (e.g., picture naming). For instance, regions within dorsal occipital cortex, posterior parietal cortex, through to the anterior intraparietal sulcus, are automatically activated when participants observe manipulable objects (e.g., Chao & Martin 2000 , Fang & He 2005 ). Those regions are important for determining volumetric and spatial information about objects as well as shaping and transporting the hand for object grasping ( Binkofski et al. 1998 , Culham et al. 2003 , Frey et al. 2005). However, those dorsal occipital and posterior parietal regions are not thought to be critical for object identification or naming (e.g., Goodale & Milner 1992 ). Naming tools also differentially activates the left inferior parietal lobule (e.g., Mahon et al. 2007 , Rumiati et al. 2004 ), a region that is important for representing complex object-associated manipulations (e.g., for review, see Johnson-Frey 2004 , Lewis 2006 ).

One clear way in which functional imaging data have contributed beyond lesion evidence to our understanding of category specificity in the brain is the description of highly consistent topographic biases by semantic categories in the ventral object–processing stream (see Figure 3 b , c ; for reviews, see Bookheimer 2002 , Gerlach 2007 , Grill-Spector & Malach 2004 , Op de Beeck et al. 2008 , Thompson-Schill 2003 ). As opposed to the anterior-posterior mapping of semantic categories within the ventral stream described by the lesion evidence (e.g., Damasio et al. 1996 ), there is also a lateral-to-medial organization. The fusiform gyrus on the ventral surface of temporal-occipital cortex is critical for representing object color and form (e.g., Martin 2007 , Miceli et al. 2001 ). Living animate things such as faces and animals elicit differential neural responses in the lateral fusiform gyrus, whereas nonliving things (tools, vehicles) elicit differential neural responses in the medial fusiform gyrus (e.g., Chao et al. 1999 , Mahon et al. 2007 , Noppeney et al. 2006 ). Stimuli that are highly definable in terms of their spatial context, such as houses and scenes, differentially activate regions anterior to these fusiform regions, in the vicinity of parahip-pocampal cortex (e.g., Bar & Aminoff 2003 , Epstein & Kanwisher 1998 ). Other visual stimuli also elicit consistent topographical biases in the ventral stream, such as written words (see Dehaene et al. 2005 for discussion) and images of body parts (e.g., Downing et al. 2001 ).

HOW DOES THE ANATOMY OF CATEGORY SPECIFICITY INFORM COGNITIVE THEORY?

The existence of category specificity in the normal brain reduces confidence in theories that reject the neural structure principle. However, those functional imaging data are also relevant for adjudicating among theories based on the neural structure principle, in that different aspects of the functional imaging evidence sit more or less naturally with the distributed domain–specific hypothesis and the sensory/functional theory.

Tool Stimuli Differentially Activate Dorsal Stream Structures Involved in Object-Directed Action

The activation by tool stimuli of regions of the brain that mediate object-directed action has been argued to follow naturally from the sensory/functional theory. On that theory, the activation of dorsal structures by tool stimuli indexes the critical role of function knowledge in the recognition of nonliving things (e.g., Boronat et al. 2004 , Kellenbach et al. 2003 , Martin et al. 2000 , Noppeney et al. 2006 , Simmons & Barsalou 2003 ). That argument is weakened, however, in the measure to which it is demonstrated that the integrity of action knowledge is not necessary in order to have other types of knowledge about tools, such as knowledge of their function.

The neuropsychological phenomenon of apraxia offers a way of testing whether action knowledge is critical for supporting conceptual processing of tools. Apraxia refers to an impairment for using objects that cannot be explained by a deficit in visual object recognition or an impairment to low-level motor processes themselves. Figure 4 a summarizes the performance profile of a patient (reported by Ochipa et al. 1989 ) who was impaired for using objects but was relatively preserved for naming the same objects [see Figure 4 b for similar dissociations in a series of single case analyses ( Negri et al. 2007 ); see also Rosci et al. (2003) ; for clear cases studies, see Moreaud et al. (1998) , Rapcsak et al. (2005), Rumiati et al. (2001) ; see Rothi et al. (1991) for an influential cognitive model; for review, see Johnson-Frey (2004) , Mahon & Caramazza (2005) ]. Apraxic deficits for using objects are often observed subsequent to lesions in the regions of the dorsal stream (in particular, the left inferior parietal lobule), reviewed above, that are automatically activated when participants name tools. The fact that apraxic patients may be able to name objects that they cannot use indicates that the activation of those regions during naming tasks is not, in and of itself, necessary for successful completion of the task. At the same time, lesions to parietal cortex, in the context of lesions to the middle temporal gyrus and frontal regions, do modulate performance in object identification. In a recent analysis ( Mahon et al. 2007 ), a group of unilateral stroke patients was separated into two groups according to the anatomical criterion of having lesions involving ( Figure 4 c , middle left ) or not involving parietal cortex ( Figure 4 c , middle right ). There was a relationship between performance in object identification and object use at the group level only in patients with lesions involving parietal cortex, a finding that suggests that action knowledge associated with objects is relevant for successful identification.

Other neuropsychological data indicate that the integrity of action knowledge is not necessary in order for patients to have accurate knowledge of object function. Figure 4d depicts the performance of patient WC ( Buxbaum et al. 2000 ) on two picture-matching tasks. In a picture-matching task that required knowledge of object manipulation, performance was impaired; however, in a picture-matching task that required knowledge of object function, performance was spared. Functional imaging studies ( Boronat et al. 2004 , Canessa et al. 2008 , Kellenbach et al. 2003 ) converge with those neuropsychological data in showing that manipulation but not function knowledge modulates neural responses in the inferior parietal lobule. There is also evidence, from both functional neuroimaging (e.g., Canessa et al. 2008 ) and neuropsychology (e.g., Sirigu et al. 1991 ), that temporal and not parietal cortex may be involved in the representation of function knowledge of objects.

The convergence between the neuropsychological evidence from apraxia and the functional-imaging evidence indicates that although a dedicated system exists for knowledge of object manipulation, that system is not critically involved in representing knowledge of object function. This suggests that the automatic engagement of action processing by manipulable objects, as observed in neuroimaging, may have consequences for a theory of pragmatics and/or action, but not necessarily for a theory of semantics ( Goodale & Milner 1992 , Jeannerod & Jacob 2005 ). This in turn weakens the claim that automatic activation of dorsal stream structures by manipulable objects is evidence for the sensory/functional theory.

Category Specificity Within the Ventral Stream

One finding from functional neuroimaging that sits more naturally with the distributed domain–specific hypothesis than the sensory/functional theory is the fact that ventral temporal cortex shows topographic biases by semantic category. In order to explain those data within the context of the sensory/functional theory, further assumptions are necessary about why there would be an organization by semantic category within the (putative) visual modality. In short, a hybrid model is required that combines the assumption of multiple semantics with some claim about how information would come to be topographically segregated by semantic category. A number of such proposals have been advanced, although not always in the context of the sensory/functional theory or more generally within the context of theories that emerge from category-specific semantic deficits (see, e.g., Gauthier et al. 2000 , Haxby et al. 2001 , Ishai et al. 1999 , Levy et al. 2001 , Mechelli et al. 2006 , Rogers et al. 2005 ). All of those proposals share the view that dimensions defined over visual information generate the observed effects of category specificity in the ventral stream.

An alternative framework (see Mahon et al. 2007 ) is that category specificity in the ventral stream is not the result of only bottom-up processes operating locally over visual information. Rather, the organization of the ventral stream is just one manifestation of a network that includes many other regions. Such a connectivity-constrained account ( Riesenhuber 2007 ) of category specificity is theoretically neutral regarding the issue of whether or not innately specified constraints determine such connectivity. For instance, although there is neural specificity for both written words and faces in regions of the ventral stream, face recognition—but not reading—could have a direct evolutionarily relevant history. Yet, it may be that neural specificity for written words in the ventral stream is driven by functional connectivity that relates visual processing to phonological processing (see Buchel et al. 1998 for relevant findings, and Dehaene et al. 2005 and Martin 2006 for discussion).

A connectivity-constrained account would offer a natural explanation for how category effects within ventral temporal cortex could be driven by nonvisual properties of the stimuli. For instance, Martin & Weisberg (2003) showed that different types of motion carried by the same geometrical shapes can drive responses in a category-specific manner in ventral temporal cortex. These findings are surprising because ventral temporal-occipital cortex is not itself motion sensitive ( Beauchamp et al. 2003 ). In the same line, Mahon and colleagues (2007) found that neural responses for manipulable objects in the medial fusiform gyrus are driven by action-related properties of objects even though action knowledge is not itself represented in the fusiform gyrus. A connectivity constrained account also offers a natural account for why structures involved in affective processing and mental state attribution should be part of the network that is activated when information about living animate things is processed (for early discussion, see Caramazza & Shelton 1998 ; for findings from fMRI, see e.g. Martin & Weisberg 2003 , Mitchell et al. 2002 , Morris et al. 1999 , Pasley et al. 2004 ).

It is unlikely that a single dimension will explain all aspects of the organization of the ventral object–processing stream. In particular, it may be the case that neural specificity for some stimulus types will be determined by qualitatively different types of constraints than neural specificity for other stimulus types. A recent study ( Polk et al. 2007 ) investigated this issue by studying the similarity in neural responses to faces, houses, pseudowords, and chairs in monozygotic and dizygotic twins and in unrelated participants. The authors found that face-and place-related responses within face- and place-selective regions, respectively, were significantly more similar for monozygotic than for dizygotic twins. However, there was no difference between the two twin groups for written words in regions that responded selectively to written words. Those data demonstrate innate constraints on the patterns of neural responses to faces and places in regions of the ventral stream selective for those categories. Future research is required to address how innate factors influence neural specificity within the ventral object–processing stream and the organization of object knowledge in the brain more generally.

THE RELATION BETWEEN SENSORY, MOTOR, AND CONCEPTUAL KNOWLEDGE

Early formulations of the sensory/functional theory assumed that conceptual content, although tied in important ways to the sensory and motor systems, was more abstract than the token-based information contained within the sensory and motor systems ( Warrington & McCarthy 1983 , 1987 ; Warrington & Shallice 1984 ; see also Crutch & Warrington 2003 ). More recent formulations of the multiple-semantics approach have argued, within the embodied cognition framework, that conceptual content can be reductively grounded in sensory and motor processes (e.g., Barsalou 1999 , 2008 ; H. Damasio et al. 2004 ; Gallese & Lakoff 2005 ; Prinz 2002 ; Pulvermüller 2005 ; Zwaan 2004 ; see also Patterson et al. 2007 ).

The first detailed articulation of the embodied cognition framework was by Allen Allport (1985) , who proposed that conceptual knowledge is organized according to sensory and motor modalities and that the information represented within different modalities was format specific:

The essential idea is that the same neural elements that are involved in coding the sensory attributes of a (possibly unknown) object presented to eye or hand or ear also make up the elements of the auto-associated activity-patterns that represent familiar object-concepts in “semantic memory.” This model is, of course, in radical opposition to the view, apparently held by many psychologists, that “semantic memory” is represented in some abstract, modality-independent, “conceptual” domain remote from the mechanisms of perception and motor organization. ( Allport 1985 , p. 53; emphasis in original)

One type of evidence, discussed above, that has been argued to support an embodied representation of object concepts is the observation that regions of the brain that directly mediate object-directed action are automatically activated when participants observe manipulable objects. However, the available neuropsychological evidence ( Figure 4 ) reduces confidence in the claim that action knowledge plays a critical role in grounding the diverse types of knowledge that we have about tools. The strongest evidence for the relevance of motor and perceptual processes to conceptual processing is provided by demonstrations that the sensory and motor systems are automatically engaged by linguistic stimuli that imply action (e.g., Boulenger et al. 2006 , Buccino et al. 2005 , Glenberg & Kaschak 2002 , Oliveri et al. 2004 ). It has also been demonstrated that activation of the motor system automatically spreads to conceptual and perceptual levels of processing (e.g., Pulvermüller et al. 2005 ).

The embodied cognition hypothesis makes strong predictions about the integrity of conceptual processes after damage to sensory and motor processes. It predicts, necessarily, and as Allport wrote, that “ … the loss of particular attribute information in semantic memory should be accompanied by a corresponding perceptual (agnostic) deficit.” (1985, p. 55; emphasis in original). Although there are long traditions within neuropsychology of studying patients with deficits for sensory and/or motor knowledge, only recently have those deficits been of such clear theoretical relevance to hypotheses about the nature of semantic memory. Systematic and theoretically informed studies of such patients will play a pivotal role in evaluating the relation between sensory, motor, and conceptual knowledge. Central to that enterprise will be to specify how information is dynamically exchanged between systems in the context of specific task requirements. This will be important for determining the degree to which sensory and motor activation is in fact a critical component of conceptual processing (see Machery 2007 , Mahon & Caramazza 2008 for discussion). It is theoretically possible (and in our view, likely) that although concepts are not exhausted by sensory and motor information, the organization of abstract concepts is nonetheless shaped in important ways by the structure of the sensory and motor systems. It is also likely, in our view, that processing of such abstract conceptual content is heavily interlaced with activation of the sensory and motor systems.

TOWARD A SYNTHESIS

We have organized this review around theoretical explanations of category specificity in the human brain. One theme that emerges is the historical progression from theories based on a single principle of organization to theories that integrate multiple dimensions of organization. This progression is due to the broad recognition in the field that a single dimension will not be sufficient to explain all aspects of the organization of object knowledge in the brain. However, not every dimension or principle of organization is of equal importance because not all dimensions have the same explanatory scope. A relative hierarchy of principles is therefore necessary to determine which of the many known facts are theoretically important and which are of only marginal significance.

Two broad findings emerge from cognitive neuropsychological research. First, patients have been reported with disproportionate impairments for a modality or type of knowledge (e.g., visual/perceptual knowledge, Figure 2 b ; manipulation knowledge, Figure 4 ). Second, category-specific semantic deficits are associated with impairments for all types of knowledge about the impaired category ( Figure 2 a ). Analogues to those two facts are also found in functional neuroimaging. First, the attributes of some categories of objects (e.g., tools) are differentially represented in modality-specific systems (i.e., motor systems). Second, within a given modality-specific system (e.g., ventral visual pathway), there is functional organization by semantic category (e.g., living animate versus nonliving) (see Figure 3 for an overview). Thus, across both neuropsychological studies and functional imaging studies, the broad empirical generalization emerges that there are two, orthogonal, constraints on the organization of object knowledge: object domain and sensory/motor modality. This empirical generalization is neutral with respect to how one explains the causes of category-specific effects in both functional neuroimaging and neuropsychology.

Many theoretical proposals of the causes of category specificity articulate dimensions along which semantic categories differ (e.g., Cree & McRae 2003 , Devlin et al. 1998 , Gauthier et al. 2000 , Haxby et al. 2001 , Humphreys & Forde 2001 , Laws & Gale 2002 , Levy et al. 2001 , Mechelli et al. 2006 , Op de Beeck et al. 2008 , Rogers et al. 2004 , Sartori & Lombardi 2004 , Simmons & Barsalou 2003 , Tranel et al. 1997 , Tyler & Moss 2001 , Warrington & Shallice 1984 , Zannino et al. 2006 ). Understanding the role that such dimensions play in the genesis of category specificity in a particular part of the brain, or a particular component of a cognitive model, will be central to characterizing the functioning of that component of the system. However, progress in understanding the causes of category specificity in one region of the brain, or one functional component of a cognitive model, will require an understanding of how category specificity is realized throughout the whole brain and throughout the whole cognitive model.

All current theories of the organization of conceptual knowledge assume that a concept is composed of distinct types of information. This shared assumption permits an explanation of how thinking about a single concept (e.g., hammer) can engage different regions of the brain that process distinct types of information (e.g., sensory versus motor). It also allows for an account of how patients may present with impairments for a type or modality of knowledge (e.g., know what a hammer looks like but not know how to use it). However, that assumption begs the question of how the different types of information that constitute a given concept are functionally unified. A central theoretical issue to be addressed by the field is to understand the nature of the mechanisms that unify different types of knowledge about the same entity in the world and that give rise to a functionally unitary concept of that entity.

Our own view—the distributed domain-specific hypothesis—assumes that the first-order principle of organization is object domain. Within any given domain of knowledge, there will be functional and neural specialization according to types or modalities of knowledge. For instance, visual motion properties of living animate things are represented in a different region/system than are visual form properties of living animate things. In addition, affective properties of living animate things may be represented by other, functionally and neuroanatomically, distinct systems. However, all of those types of information constitute the domain “living animate.” For that reason, it is critical to specify the nature of the functional connectivity that relates processing across distinct subsystems specialized for different types of information. The basic expectation of the distributed domain-specific hypothesis is that the functional connectivity that relates processing across distinct types of information (e.g., emotional value versus visual form) will be concentrated around those domains that have had evolutionarily important histories. The strong prediction that follows from that view is that such neural circuits are the same circuits that are damaged in patients with category-specific semantic deficits.

Independently of whether the distributed domain-specific hypothesis is empirically confirmed, it serves to highlight two key aspects of human conceptual processing. First, humans do not have systems that support rich conceptual knowledge of objects in order to carry out only explicit knowledge tasks, such as object naming or similarity judgments. We have those systems because they serve action and ultimately have been in the service of survival. An understanding of the architecture of the conceptual system must therefore be situated in the context of the real-world computational problems that the conceptual system is structured to support. Second, human behavior arises due to the integration of multiple cognitive processes that individually operate over distinct types of knowledge. In contrast to the view that domain specificity implies modularity, we have emphasized the distributed nature of domain-specific neural circuits. On the distributed domain-specific hypothesis, the distinct (and potentially modular) processes within the sensory, motor, and affective systems are components of broader structures within the mind/brain. This framework thus emphasizes the need to understand how different types of cognitive processes, operating over different types of information, work in concert to orchestrate behavior.

In the more than 25 years since Warrington and colleagues’ first detailed reports of patients with category-specific semantic deficits, new fields of investigation have emerged around the study of the organization and representation of conceptual knowledge. Despite that progress, the theoretical questions that currently occupy researchers are the same as those that were initially framed and debated two decades ago: What are the principles of neural organization that give rise to effects of category specificity? Are different types of information involved in processing different semantic categories and, if so, what distinguishes those different types of information? Future research will undoubtedly build upon the currently available theories as well as redeploy their individual assumptions within new theoretical frameworks.

FUTURE DIRECTIONS

To what degree do sensory and motor processes participate in higher cognitive function? The available evidence from neuropsychology places a clear upper limit on the degree to which conceptual knowledge can be assumed to be “embodied.” However, equally compelling findings from functional neuroimaging demonstrate that the sensory and motor systems are automatically engaged during conceptual processing. It will be important to develop articulated models of the dynamics of activation flow among concepts and the sensory and motor systems in order to test hypotheses about the causes of sensory and motor activation during conceptual processing.
Are different domains of knowledge represented differently in males and females? Some researchers have highlighted the fact that patients with disproportionate semantic impairments for fruit/vegetables are male. This pattern remains even after controlling for gender-specific familiarity among items from different categories. Those data raise the question of whether early (and culturally influenced) differences in experience can qualitatively shape the functional architecture of the conceptual system.
How does damage to one region of the brain affect processing in other regions of the brain? Little is currently known about how damage to distinct regions within a network affects processing in other regions of the network. Detailed cognitive and anatomical studies of patients with semantic deficits will aide in understanding the dynamics of brain damage and the implications for cognitive models of conceptual processing.

Acknowledgments

Preparation of this article was supported in part by a National Science Foundation Graduate Research Fellowship to BZM, National Institutes of Health grant DC04542 to AC, and by a grant from the Fondazione Cassa di Risparmio di Trento e Rovereto. The authors are grateful to Erminio Capitani, Marcella Laiacona, Alex Martin, and Daniel Schacter for their comments on an earlier draft.

DISCLOSURE STATEMENT

The authors are not aware of any biases that might be perceived as affecting the objectivity of this review.

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Developmental Psychology 101: Theories, Stages, & Research

You can imagine how vast this field of psychology is if it has to cover the whole of life, from birth through death.

Just like any other area of psychology, it has created exciting debates and given rise to fascinating case studies.

In recent years, developmental psychology has shifted to incorporate positive psychology paradigms to create a holistic lifespan approach. As an example, the knowledge gained from positive psychology can enhance the development of children in education.

In this article, you will learn a lot about different aspects of developmental psychology, including how it first emerged in history and famous theories and models.

Before you continue, we thought you might like to download our three Positive Psychology Exercises for free . These science-based exercises explore fundamental aspects of positive psychology, including strengths, values, and self-compassion, and will give you the tools to enhance the wellbeing of your clients, students, or employees.

This Article Contains:

What is developmental psychology, 4 popular theories, stages, & models, 2 questions and research topics, fascinating case studies & research findings, a look at positive developmental psychology, applying developmental psychology in education, resources from positivepsychology.com, a take-home message.

Human beings change drastically over our lifetime.

The American Psychological Association (2020) defines developmental psychology as the study of physical, mental, and behavioral changes, from conception through old age.

Developmental psychology investigates biological, genetic, neurological, psychosocial, cultural, and environmental factors of human growth (Burman, 2017).

Over the years, developmental psychology has been influenced by numerous theories and models in varied branches of psychology (Burman, 2017).

History of developmental psychology

Developmental psychology first appeared as an area of study in the late 19th century (Baltes, Lindenberger, & Staudinger, 2007). Developmental psychology focused initially on child and adolescent development, and was concerned about children’s minds and learning (Hall, 1883).

There are several key figures in developmental psychology. In 1877, the famous evolutionary biologist Charles Darwin undertook the first study of developmental psychology on innate communication forms. Not long after, physiologist William Preyer (1888) published a book on the abilities of an infant.

The 1900s saw many significant people dominating the developmental psychology field with their detailed theories of development: Sigmund Freud (1923, 1961), Jean Piaget (1928), Erik Erikson (1959), Lev Vygotsky (1978), John Bowlby (1958), and Albert Bandura (1977).

By the 1920s, the scope of developmental psychology had begun to include adult development and the aging process (Thompson, 2016).

In more recent years, it has broadened further to include prenatal development (Brandon et al., 2009). Developmental psychology is now understood to encompass the complete lifespan (Baltes et al., 2007).

Each of these models has contributed to the understanding of the process of human development and growth.

Furthermore, each theory and model focuses on different aspects of development: social, emotional, psychosexual, behavioral, attachment, social learning, and many more.

Here are some of the most popular models of development that have heavily contributed to the field of developmental psychology.

1. Bowlby’s attachment styles

The seminal work of psychologist John Bowlby (1958) showcased his interest in children’s social development. Bowlby (1969, 1973, 1980) developed the most famous theory of social development, known as attachment theory .

Bowlby (1969) hypothesized that the need to form attachments is innate, embedded in all humans for survival and essential for children’s development. This instinctive bond helps ensure that children are cared for by their parent or caregiver (Bowlby, 1969, 1973, 1980).

Bowlby’s original attachment work was developed further by one of his students, Mary Ainsworth. She proposed several attachment styles between the child and the caregiver (Ainsworth & Bell, 1970).

This theory clearly illustrates the importance of attachment styles to a child’s future development. Consistent and stable caregiving results in a secure attachment style (Ainsworth, Blehar, Waters, & Wall, 1978). In contrast, unstable and insecure caregiving results in several negative attachment styles: ambivalent, avoidant, or disorganized (Ainsworth & Bell, 1970; Main & Solomon, 1986).

Bowlby’s theory does not consider peer group influence or how it can shape children’s personality and development (Harris, 1998).

2. Piaget’s stage theory

Jean Piaget was a French psychologist highly interested in child development. He was interested in children’s thinking and how they acquire, construct, and use their knowledge (Piaget, 1951).

Piaget’s (1951) four-stage theory of cognitive development sequences a child’s intellectual development. According to this theory, all children move through these four stages of development in the same order (Simatwa, 2010).

The sensorimotor stage is from birth to two years old. Behaviors are triggered by sensory stimuli and limited to simple motor responses. If an object is removed from the child’s vision, they think it no longer exists (Piaget, 1936).

The pre-operational stage occurs between two and six years old. The child learns language but cannot mentally manipulate information or understand concrete logic (Wadsworth, 1971).

The concrete operational stage takes place from 7 to 11 years old. Children begin to think more logically about factual events. Abstract or hypothetical concepts are still difficult to understand in this stage (Wadsworth, 1971).

In the formal operational stage from 12 years to adulthood, abstract thought and skills arise (Piaget, 1936).

Piaget did not consider other factors that might affect these stages or a child’s progress through them. Biological maturation and interaction with the environment can determine the rate of cognitive development in children (Papalia & Feldman, 2011). Individual differences can also dictate a child’s progress (Berger, 2014).

3. Freud’s psychosexual development theory

One of the most influential developmental theories, which encompassed psychosexual stages of development, was developed by Austrian psychiatrist Sigmund Freud (Fisher & Greenberg, 1996).

Freud concluded that childhood experiences and unconscious desires influence behavior after witnessing his female patients experiencing physical symptoms and distress with no physical cause (Breuer & Freud, 1957).

According to Freud’s psychosexual theory, child development occurs in a series of stages, each focused on different pleasure areas of the body. During each stage, the child encounters conflicts, which play a significant role in development (Silverman, 2017).

Freud’s theory of psychosexual development includes the oral, anal, phallic, latent, and genital stages. His theory suggests that the energy of the libido is focused on these different erogenous zones at each specific stage (Silverman, 2017).

Freud concluded that the successful completion of each stage leads to healthy adult development. He also suggested that a failure to progress through a stage causes fixation and developmental difficulties, such as nail biting (oral fixation) or obsessive tidiness (anal fixation; Silverman, 2017).

Freud considered personality to be formed in childhood as a child passes through these stages. Criticisms of Freud’s theory of psychosexual development include its failure to consider that personality can change and grow over an entire lifetime. Freud believed that early experiences played the most significant role in shaping development (Silverman, 2017).

4. Bandura’s social learning theory

American psychologist Albert Bandura proposed the social learning theory (Bandura, Ross, & Ross, 1961). Bandura did not believe that classical or operant conditioning was enough to explain learned behavior because some behaviors of children are never reinforced (Bandura, 1986). He believed that children observe, imitate, and model the behaviors and reactions of others (Bandura, 1977).

Bandura suggested that observation is critical in learning. Further, the observation does not have to be of a live actor, such as in the Bobo doll experiment (Bandura, 1986). Bandura et al. (1961) considered that learning and modeling can also occur from listening to verbal instructions on behavior performance.

Bandura’s (1977) social theory posits that both environmental and cognitive factors interact to influence development.

Bandura’s developmental theory has been criticized for not considering biological factors or children’s autonomic nervous system responses (Kevin, 1995).

Overview of theories of development – Khan Academy

Developmental psychology has given rise to many debatable questions and research topics. Here are two of the most commonly discussed.

1. Nature vs nurture debate

One of the oldest debates in the field of developmental psychology has been between nature and nurture (Levitt, 2013).

Is human development a result of hereditary factors (genes), or is it influenced by the environment (school, family, relationships, peers, community, culture)?

The polarized position of developmental psychologists of the past has now changed. The nature/nurture question now concerns the relationship between the innateness of an attribute and the environmental effects on that attribute (Nesterak, 2015).

The field of epigenetics describes how behavioral and environmental influences affect the expression of genes (Kubota, Miyake, & Hirasawa, 2012).

Many severe mental health disorders have a hereditary component. Yet, the environment and behavior, such as improved diet, reduced stress, physical activity, and a positive mindset, can determine whether this health condition is ever expressed (Śmigielski, Jagannath, Rössler, Walitza, & Grünblatt, 2020).

When considering classic models of developmental psychology, such as Piaget’s schema theory and Freud’s psychosexual theory, you’ll see that they both perceive development to be set in stone and unchangeable by the environment.

Contemporary developmental psychology theories take a different approach. They stress the importance of multiple levels of organization over the course of human development (Lomas, Hefferon, & Ivtzan, 2016).

2. Theory of mind

Theory of mind allows us to understand that others have different intentions, beliefs, desires, perceptions, behaviors, and emotions (American Psychological Association, 2020).

It was first identified by research by Premack and Woodruff (1978) and considered to be a natural developmental stage of progression for all children. Starting around the ages of four or five, children begin to think about the thoughts and feelings of others. This shows an emergence of the theory of mind (Wellman & Liu, 2004).

However, the ability of all individuals to achieve and maintain this critical skill at the same level is debatable.

Children diagnosed with autism exhibit a deficit in the theory of mind (Baron-Cohen, Leslie, & Frith, 1985).

Individuals with depression (psychotic and non-psychotic) are significantly impaired in theory of mind tasks (Wang, Wang, Chen, Zhu, & Wang, 2008).

People with social anxiety disorder have also been found to show less accuracy in decoding the mental states of others (Washburn, Wilson, Roes, Rnic, & Harkness, 2016).

Further research has shown that the theory of mind changes with aging. This suggests a developmental lifespan process for this concept (Meinhardt-Injac, Daum, & Meinhardt, 2020).

1. Little Albert

The small child who was the focus of the experiments of behavioral psychologists Watson and Rayner (1920) was referred to as ‘Little Albert.’ These experiments were essential landmarks in developmental psychology and showed how an emotionally stable child can be conditioned to develop a phobia.

Albert was exposed to several neutral stimuli including cotton wool, masks, a white rat, rabbit, monkey, and dog. Albert showed no initial fear to these stimuli.

When a loud noise was coupled with the initially neutral stimulus, Albert became very distressed and developed a phobia of the object, which extended to any similar object as well.

This experiment highlights the importance of environmental factors in the development of behaviors in children.

2. David Reimer

At the age of eight months, David Reimer lost his penis in a circumcision operation that went wrong. His worried parents consulted a psychologist, who advised them to raise David as a girl.

David’s young age meant he knew nothing about this. He went through the process of hormonal treatment and gender reassignment. At the age of 14, David found out the truth and wanted to reverse the gender reassignment process to become a boy again. He had always felt like a boy until this time, even though he was socialized and brought up as a girl (Colapinto, 2006).

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Contemporary theories of developmental psychology often encompass a holistic approach and a more positive approach to development.

Positive psychology has intersected with developmental disciplines in areas such as parenting, education, youth, and aging (Lomas et al., 2016).

These paradigms can all be grouped together under the umbrella of positive developmental psychology. This fresh approach to development focuses on the wellbeing aspects of development, while systematically bringing them together (Lomas, et al., 2016).

Positive parenting is the approach to children’s wellbeing by focusing on the role of parents and caregivers (Latham, 1994).
Positive education looks at flourishing in the context of school (Seligman, Ernst, Gillham, Reivich, & Linkins, 2009).
Positive youth development is the productive and constructive focus on adolescence and early adulthood to enhance young people’s strengths and promote positive outcomes (Larson, 2000).
Positive aging , also known as healthy aging, focuses on the positivity of aging as a healthy, normal stage of life (Vaillant, 2004).

Much of the empirical and theoretical work connected to positive developmental psychology has been going on for years, even before the emergence of positive psychology itself (Lomas et al., 2016).

We recommend this related article Applying Positive Psychology in Schools & Education: Your Ultimate Guide for further reading.

In the classroom, developmental psychology considers children’s psychological, emotional, and intellectual characteristics according to their developmental stage.

A report on the top 20 principles of psychology in the classroom, from pre-kindergarten to high school, was published by the American Psychological Association in 2015. The report also advised how teachers can respond to these principles in the classroom setting.

The top 5 principles and teacher responses are outlined in the table below.

There are many valuable resources to help you foster positive development no matter whether you’re working with young children, teenagers, or adults.

To help get you started, check out the following free resources from around our blog.

Adopt A Growth Mindset This exercise helps clients recognize instances of fixed mindset in their thinking and actions and replace them with thoughts and behaviors more supportive of a growth mindset.
Childhood Frustrations This worksheet provides a space for clients to document key challenges experienced during childhood, together with their emotional and behavioral responses.
What I Want to Be This worksheet helps children identify behaviors and emotions they would like to display and select an opportunity in the future to behave in this ideal way.
17 Positive Psychology Exercises If you’re looking for more science-based ways to help others enhance their wellbeing, this signature collection contains 17 validated positive psychology tools for practitioners. Use them to help others flourish and thrive.
Developmental Psychology Courses If you are interested in a career in Developmental Psychology , we suggest 15 of the best courses in this article.

17 Top-Rated Positive Psychology Exercises for Practitioners

Expand your arsenal and impact with these 17 Positive Psychology Exercises [PDF] , scientifically designed to promote human flourishing, meaning, and wellbeing.

Created by Experts. 100% Science-based.

Earlier developmental psychology models and theories were focused on specific areas, such as attachment, psychosexual, cognitive, and social learning. Although informative, they did not take in differing perspectives and were fixed paradigms.

We’ve now come to understand that development is not fixed. Individual differences take place in development, and the factors that can affect development are many. It is ever changing throughout life.

The modern-day approach to developmental psychology includes sub-fields of positive psychology. It brings these differing disciplines together to form an overarching positive developmental psychology paradigm.

Developmental psychology has helped us gain a considerable understanding of children’s motivations, social and emotional contexts, and their strengths and weaknesses.

This knowledge is essential for educators to create rich learning environments for students to help them develop positively and ultimately flourish to their full potential.

We hope you enjoyed reading this article. Don’t forget to download our three Positive Psychology Exercises for free .

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Developmental Psychology

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Huang Silin & Zhu Bi

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Silin, H., Bi, Z. (2024). Developmental Psychology. In: The ECPH Encyclopedia of Psychology. Springer, Singapore. https://doi.org/10.1007/978-981-99-6000-2_432-1

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Research in Developmental Psychology

What you’ll learn to do: examine how to do research in lifespan development.

Desk shown from above, pair of hands seen gesturing towards a graph

How do we know what changes and stays the same (and when and why) in lifespan development? We rely on research that utilizes the scientific method so that we can have confidence in the findings. How data are collected may vary by age group and by the type of information sought. The developmental design (for example, following individuals as they age over time or comparing individuals of different ages at one point in time) will affect the data and the conclusions that can be drawn from them about actual age changes. What do you think are the particular challenges or issues in conducting developmental research, such as with infants and children? Read on to learn more.

Learning outcomes

Explain how the scientific method is used in researching development
Compare various types and objectives of developmental research
Describe methods for collecting research data (including observation, survey, case study, content analysis, and secondary content analysis)
Explain correlational research
Describe the value of experimental research
Compare the advantages and disadvantages of developmental research designs (cross-sectional, longitudinal, and sequential)
Describe challenges associated with conducting research in lifespan development

Research in Lifespan Development

How do we know what we know.

An important part of learning any science is having a basic knowledge of the techniques used in gathering information. The hallmark of scientific investigation is that of following a set of procedures designed to keep questioning or skepticism alive while describing, explaining, or testing any phenomenon. Not long ago a friend said to me that he did not trust academicians or researchers because they always seem to change their story. That, however, is exactly what science is all about; it involves continuously renewing our understanding of the subjects in question and an ongoing investigation of how and why events occur. Science is a vehicle for going on a never-ending journey. In the area of development, we have seen changes in recommendations for nutrition, in explanations of psychological states as people age, and in parenting advice. So think of learning about human development as a lifelong endeavor.

Personal Knowledge

How do we know what we know? Take a moment to write down two things that you know about childhood. Okay. Now, how do you know? Chances are you know these things based on your own history (experiential reality), what others have told you, or cultural ideas (agreement reality) (Seccombe and Warner, 2004). There are several problems with personal inquiry or drawing conclusions based on our personal experiences.

Our assumptions very often guide our perceptions, consequently, when we believe something, we tend to see it even if it is not there. Have you heard the saying, “seeing is believing”? Well, the truth is just the opposite: believing is seeing. This problem may just be a result of cognitive ‘blinders’ or it may be part of a more conscious attempt to support our own views. Confirmation bias is the tendency to look for evidence that we are right and in so doing, we ignore contradictory evidence.

Philosopher Karl Popper suggested that the distinction between that which is scientific and that which is unscientific is that science is falsifiable; scientific inquiry involves attempts to reject or refute a theory or set of assumptions (Thornton, 2005). A theory that cannot be falsified is not scientific. And much of what we do in personal inquiry involves drawing conclusions based on what we have personally experienced or validating our own experience by discussing what we think is true with others who share the same views.

Science offers a more systematic way to make comparisons and guard against bias. One technique used to avoid sampling bias is to select participants for a study in a random way. This means using a technique to ensure that all members have an equal chance of being selected. Simple random sampling may involve using a set of random numbers as a guide in determining who is to be selected. For example, if we have a list of 400 people and wish to randomly select a smaller group or sample to be studied, we use a list of random numbers and select the case that corresponds with that number (Case 39, 3, 217, etc.). This is preferable to asking only those individuals with whom we are familiar to participate in a study; if we conveniently chose only people we know, we know nothing about those who had no opportunity to be selected. There are many more elaborate techniques that can be used to obtain samples that represent the composition of the population we are studying. But even though a randomly selected representative sample is preferable, it is not always used because of costs and other limitations. As a consumer of research, however, you should know how the sample was obtained and keep this in mind when interpreting results. It is possible that what was found was limited to that sample or similar individuals and not generalizable to everyone else.

Scientific Methods

The particular method used to conduct research may vary by discipline and since lifespan development is multidisciplinary, more than one method may be used to study human development. One method of scientific investigation involves the following steps:

Determining a research question
Reviewing previous studies addressing the topic in question (known as a literature review)
Determining a method of gathering information
Conducting the study
Interpreting the results
Drawing conclusions; stating limitations of the study and suggestions for future research
Making the findings available to others (both to share information and to have the work scrutinized by others)

The findings of these scientific studies can then be used by others as they explore the area of interest. Through this process, a literature or knowledge base is established. This model of scientific investigation presents research as a linear process guided by a specific research question. And it typically involves quantitative research , which relies on numerical data or using statistics to understand and report what has been studied.

Another model of research, referred to as qualitative research, may involve steps such as these:

Begin with a broad area of interest and a research question
Gain entrance into a group to be researched
Gather field notes about the setting, the people, the structure, the activities, or other areas of interest
Ask open-ended, broad “grand tour” types of questions when interviewing subjects
Modify research questions as the study continues
Note patterns or consistencies
Explore new areas deemed important by the people being observed
Report findings

In this type of research, theoretical ideas are “grounded” in the experiences of the participants. The researcher is the student and the people in the setting are the teachers as they inform the researcher of their world (Glazer & Strauss, 1967). Researchers should be aware of their own biases and assumptions, acknowledge them, and bracket them in efforts to keep them from limiting accuracy in reporting. Sometimes qualitative studies are used initially to explore a topic and more quantitative studies are used to test or explain what was first described.

A good way to become more familiar with these scientific research methods, both quantitative and qualitative, is to look at journal articles, which are written in sections that follow these steps in the scientific process. Most psychological articles and many papers in the social sciences follow the writing guidelines and format dictated by the American Psychological Association (APA). In general, the structure follows: abstract (summary of the article), introduction or literature review, methods explaining how the study was conducted, results of the study, discussion and interpretation of findings, and references.

Link to Learning

Brené Brown is a bestselling author and social work professor at the University of Houston. She conducts grounded theory research by collecting qualitative data from large numbers of participants. In Brené Brown’s TED Talk The Power of Vulnerability , Brown refers to herself as a storyteller-researcher as she explains her research process and summarizes her results.

Research Methods and Objectives

The main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Some examples of descriptive questions include:

“How much time do parents spend with their children?”
“How many times per week do couples have intercourse?”
“When is marital satisfaction greatest?”

The main types of descriptive studies include observation, case studies, surveys, and content analysis (which we’ll examine further in the module). Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. Some experimental research includes explanatory studies, which are efforts to answer the question “why” such as:

“Why have rates of divorce leveled off?”
“Why are teen pregnancy rates down?”
“Why has the average life expectancy increased?”

Evaluation research is designed to assess the effectiveness of policies or programs. For instance, research might be designed to study the effectiveness of safety programs implemented in schools for installing car seats or fitting bicycle helmets. Do children who have been exposed to the safety programs wear their helmets? Do parents use car seats properly? If not, why not?

Research Methods

We have just learned about some of the various models and objectives of research in lifespan development. Now we’ll dig deeper to understand the methods and techniques used to describe, explain, or evaluate behavior.

All types of research methods have unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control over how or what kind of data was collected.

Types of Descriptive Research

Observation.

Observational studies , also called naturalistic observation, involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play in a park, or behind a one-way glass while children are at play in a laboratory playroom. The researcher may follow a checklist and record the frequency and duration of events (perhaps how many conflicts occur among 2-year-olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.). The researcher may be a participant or a non-participant. What would be the strengths of being a participant? What would be the weaknesses?

In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. One weakness of self-report studies is that what people do and what they say they do are often very different. A major weakness of observational studies is that they do not allow the researcher to explain causal relationships. Yet, observational studies are useful and widely used when studying children. It is important to remember that most people tend to change their behavior when they know they are being watched (known as the Hawthorne effect ) and children may not survey well.

Case Studies

Case studies involve exploring a single case or situation in great detail. Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation. Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation. And they are often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment. Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions. However, the findings from case studies cannot be generalized or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison. (Read The Man Who Mistook His Wife for a Hat by Dr. Oliver Sacks as a good example of the case study approach.)

A person is checking off boxes on a paper survey

Surveys are familiar to most people because they are so widely used. Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online. A survey involves asking a standard set of questions to a group of subjects. In a highly structured survey, subjects are forced to choose from a response set such as “strongly disagree, disagree, undecided, agree, strongly agree”; or “0, 1-5, 6-10, etc.” Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many variables in a relatively short period of time. Surveys typically yield surface information on a wide variety of factors, but may not allow for an in-depth understanding of human behavior.

Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices. However, they are based on self-report, or what people say they do rather than on observation, and this can limit accuracy. Validity refers to accuracy and reliability refers to consistency in responses to tests and other measures; great care is taken to ensure the validity and reliability of surveys.

Content Analysis

Content analysis involves looking at media such as old texts, pictures, commercials, lyrics, or other materials to explore patterns or themes in culture. An example of content analysis is the classic history of childhood by Aries (1962) called “Centuries of Childhood” or the analysis of television commercials for sexual or violent content or for ageism. Passages in text or television programs can be randomly selected for analysis as well. Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.

Secondary content analysis, or archival research, involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices, or preferences. There are a number of data sets available to those who wish to conduct this type of research. The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study. And unfortunately, the researcher is limited to the questions asked and data collected originally.

Correlational and Experimental Research

Correlational research.

When scientists passively observe and measure phenomena it is called correlational research . Here, researchers do not intervene and change behavior, as they do in experiments. In correlational research, the goal is to identify patterns of relationships, but not cause and effect. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.

So, what if you wanted to test whether spending money on others is related to happiness, but you don’t have $20 to give to each participant in order to have them spend it for your experiment? You could use a correlational design—which is exactly what Professor Elizabeth Dunn (2008) at the University of British Columbia did when she conducted research on spending and happiness. She asked people how much of their income they spent on others or donated to charity, and later she asked them how happy they were. Do you think these two variables were related? Yes, they were! The more money people reported spending on others, the happier they were.

Understanding Correlation

Scatterplot of the association between happiness and ratings of the past month, a positive correlation (r = .81)

With a positive correlation , the two variables go up or down together. In a scatterplot, the dots form a pattern that extends from the bottom left to the upper right (just as they do in Figure 1). The r value for a positive correlation is indicated by a positive number (although, the positive sign is usually omitted). Here, the r value is .81. For the example above, the direction of the association is positive. This means that people who perceived the past month as being good reported feeling happier, whereas people who perceived the month as being bad reported feeling less happy.

A negative correlation is one in which the two variables move in opposite directions. That is, as one variable goes up, the other goes down. Figure 2 shows the association between the average height of males in a country (y-axis) and the pathogen prevalence (or commonness of disease; x-axis) of that country. In this scatterplot, each dot represents a country. Notice how the dots extend from the top left to the bottom right. What does this mean in real-world terms? It means that people are shorter in parts of the world where there is more disease. The r-value for a negative correlation is indicated by a negative number—that is, it has a minus (–) sign in front of it. Here, it is –.83.

Scatterplot showing the association between average male height and pathogen prevalence, a negative correlation (r = –.83).

Experimental Research

Experiments are designed to test hypotheses (or specific statements about the relationship between variables ) in a controlled setting in an effort to explain how certain factors or events produce outcomes. A variable is anything that changes in value. Concepts are operationalized or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study. For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of marital satisfaction. What is something measurable that would indicate some level of marital satisfaction? Would it be the amount of time couples spend together each day? Or eye contact during a discussion about money? Or maybe a subject’s score on a marital satisfaction scale? Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction. What do you think? These are the kinds of considerations researchers must make when working through the design.

The experimental method is the only research method that can measure cause and effect relationships between variables. Three conditions must be met in order to establish cause and effect. Experimental designs are useful in meeting these conditions:

The independent and dependent variables must be related. In other words, when one is altered, the other changes in response. The independent variable is something altered or introduced by the researcher; sometimes thought of as the treatment or intervention. The dependent variable is the outcome or the factor affected by the introduction of the independent variable; the dependent variable depends on the independent variable. For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.
The cause must come before the effect. Experiments measure subjects on the dependent variable before exposing them to the independent variable (establishing a baseline). So we would measure the subjects’ level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels. (Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these methods.)
The cause must be isolated. The researcher must ensure that no outside, perhaps unknown variables, are actually causing the effect we see. The experimental design helps make this possible. In an experiment, we would make sure that our subjects’ diets were held constant throughout the exercise program. Otherwise, the diet might really be creating a change in stress level rather than exercise.

A basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the experimental group or the control group . Ideally, to prevent bias, the participants would be blind to their condition (not aware of which group they are in) and the researchers would also be blind to each participant’s condition (referred to as “ double blind “). The experimental group is the group that is going to be exposed to an independent variable or condition the researcher is introducing as a potential cause of an event. The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable. This helps address the placebo effect, which is that a group may expect changes to happen just by participating. After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred. If so, we are in a better position to suggest that the independent variable caused the change in the dependent variable . The basic experimental model looks like this:

The major advantage of the experimental design is that of helping to establish cause and effect relationships. A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting.

Developmental Research Designs

Now you know about some tools used to conduct research about human development. Remember, research methods are tools that are used to collect information. But it is easy to confuse research methods and research design. Research design is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how. Developmental research designs are techniques used particularly in lifespan development research. When we are trying to describe development and change, the research designs become especially important because we are interested in what changes and what stays the same with age. These techniques try to examine how age, cohort, gender, and social class impact development.

Cross-sectional designs

The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs. Cross-sectional research designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis (an educated guess, based on theory or observations) that intelligence declines as people get older. The researchers might choose to give a certain intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?

Text stating that the year of study is 2010 and an experiment looks at cohort A with 20 year olds, cohort B of 50 year olds and cohort C with 80 year olds

No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age differences not necessarily changes with age or over time. That is, although the study described above can show that in 2010, the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower on the intelligence test than the 20-year-olds, the data used to come up with this conclusion were collected from different individuals (or groups of individuals). It could be, for instance, that when these 20-year-olds get older (50 and eventually 80), they will still score just as high on the intelligence test as they did at age 20. In a similar way, maybe the 80-year-olds would have scored relatively low on the intelligence test even at ages 50 and 20; the researchers don’t know for certain because they did not follow the same individuals as they got older.

It is also possible that the differences found between the age groups are not due to age, per se, but due to cohort effects. The 80-year-olds in this 2010 research grew up during a particular time and experienced certain events as a group. They were born in 1930 and are part of the Traditional or Silent Generation. The 50-year-olds were born in 1960 and are members of the Baby Boomer cohort. The 20-year-olds were born in 1990 and are part of the Millennial or Gen Y Generation. What kinds of things did each of these cohorts experience that the others did not experience or at least not in the same ways?

You may have come up with many differences between these cohorts’ experiences, such as living through certain wars, political and social movements, economic conditions, advances in technology, changes in health and nutrition standards, etc. There may be particular cohort differences that could especially influence their performance on intelligence tests, such as education level and use of computers. That is, many of those born in 1930 probably did not complete high school; those born in 1960 may have high school degrees, on average, but the majority did not attain college degrees; the young adults are probably current college students. And this is not even considering additional factors such as gender, race, or socioeconomic status. The young adults are used to taking tests on computers, but the members of the other two cohorts did not grow up with computers and may not be as comfortable if the intelligence test is administered on computers. These factors could have been a factor in the research results.

Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently. Just think about the mindsets of participants in research that was conducted in the United States right after the terrorist attacks on September 11, 2001.

Longitudinal research designs

Middle aged woman holding own photograph of her younger self.

Longitudinal research involves beginning with a group of people who may be of the same age and background (cohort) and measuring them repeatedly over a long period of time. One of the benefits of this type of research is that people can be followed through time and be compared with themselves when they were younger; therefore changes with age over time are measured. What would be the advantages and disadvantages of longitudinal research? Problems with this type of research include being expensive, taking a long time, and subjects dropping out over time. Think about the film, 63 Up , part of the Up Series mentioned earlier, which is an example of following individuals over time. In the videos, filmed every seven years, you see how people change physically, emotionally, and socially through time; and some remain the same in certain ways, too. But many of the participants really disliked being part of the project and repeatedly threatened to quit; one disappeared for several years; another died before her 63rd year. Would you want to be interviewed every seven years? Would you want to have it made public for all to watch?

Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?

The same person, "Person A" is 20 years old in 2010, 50 years old in 2040, and 80 in 2070.

Since longitudinal research happens over a period of time (which could be short term, as in months, but is often longer, as in years), there is a risk of attrition. Attrition occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time. There is also something known as selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members, to replace those who have dropped out.

The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time, not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect. Practice effects occur when participants become better at a task over time because they have done it again and again (not due to natural psychological development). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration). Another limitation of longitudinal research is that the data are limited to only one cohort.

Sequential research designs

Sequential research designs include elements of both longitudinal and cross-sectional research designs. Similar to longitudinal designs, sequential research features participants who are followed over time; similar to cross-sectional designs, sequential research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects. In 1965, K. Warner Schaie described particular sequential designs: cross-sequential, cohort sequential, and time-sequential. The differences between them depended on which variables were focused on for analyses of the data (data could be viewed in terms of multiple cross-sectional designs or multiple longitudinal designs or multiple cohort designs). Ideally, by comparing results from the different types of analyses, the effects of age, cohort, and time in history could be separated out.

Challenges Conducting Developmental Research

The previous sections describe research tools to assess development across the lifespan, as well as the ways that research designs can be used to track age-related changes and development over time. Before you begin conducting developmental research, however, you must also be aware that testing individuals of certain ages (such as infants and children) or making comparisons across ages (such as children compared to teens) comes with its own unique set of challenges. In the final section of this module, let’s look at some of the main issues that are encountered when conducting developmental research, namely ethical concerns, recruitment issues, and participant attrition.

Ethical Concerns

You may already know that Institutional Review Boards (IRBs) must review and approve all research projects that are conducted at universities, hospitals, and other institutions (each broad discipline or field, such as psychology or social work, often has its own code of ethics that must also be followed, regardless of institutional affiliation). An IRB is typically a panel of experts who read and evaluate proposals for research. IRB members want to ensure that the proposed research will be carried out ethically and that the potential benefits of the research outweigh the risks and potential harm (psychological as well as physical harm) for participants.

What you may not know though, is that the IRB considers some groups of participants to be more vulnerable or at-risk than others. Whereas university students are generally not viewed as vulnerable or at-risk, infants and young children commonly fall into this category. What makes infants and young children more vulnerable during research than young adults? One reason infants and young children are perceived as being at increased risk is due to their limited cognitive capabilities, which makes them unable to state their willingness to participate in research or tell researchers when they would like to drop out of a study. For these reasons, infants and young children require special accommodations as they participate in the research process. Similar issues and accommodations would apply to adults who are deemed to be of limited cognitive capabilities.

When thinking about special accommodations in developmental research, consider the informed consent process. If you have ever participated in scientific research, you may know through your own experience that adults commonly sign an informed consent statement (a contract stating that they agree to participate in research) after learning about a study. As part of this process, participants are informed of the procedures to be used in the research, along with any expected risks or benefits. Infants and young children cannot verbally indicate their willingness to participate, much less understand the balance of potential risks and benefits. As such, researchers are oftentimes required to obtain written informed consent from the parent or legal guardian of the child participant, an adult who is almost always present as the study is conducted. In fact, children are not asked to indicate whether they would like to be involved in a study at all (a process known as assent) until they are approximately seven years old. Because infants and young children cannot easily indicate if they would like to discontinue their participation in a study, researchers must be sensitive to changes in the state of the participant (determining whether a child is too tired or upset to continue) as well as to parent desires (in some cases, parents might want to discontinue their involvement in the research). As in adult studies, researchers must always strive to protect the rights and well-being of the minor participants and their parents when conducting developmental research.

Recruitment

An additional challenge in developmental science is participant recruitment. Recruiting university students to participate in adult studies is typically easy. Unfortunately, young children cannot be recruited in this way. Given these limitations, how do researchers go about finding infants and young children to be in their studies?

The answer to this question varies along multiple dimensions. Researchers must consider the number of participants they need and the financial resources available to them, among other things. Location may also be an important consideration. Researchers who need large numbers of infants and children may attempt to recruit them by obtaining infant birth records from the state, county, or province in which they reside. Researchers can choose to pay a recruitment agency to contact and recruit families for them. More economical recruitment options include posting advertisements and fliers in locations frequented by families, such as mommy-and-me classes, local malls, and preschools or daycare centers. Researchers can also utilize online social media outlets like Facebook, which allows users to post recruitment advertisements for a small fee. Of course, each of these different recruitment techniques requires IRB approval. And if children are recruited and/or tested in school settings, permission would need to be obtained ahead of time from teachers, schools, and school districts (as well as informed consent from parents or guardians).

And what about the recruitment of adults? While it is easy to recruit young college students to participate in research, some would argue that it is too easy and that college students are samples of convenience. They are not randomly selected from the wider population, and they may not represent all young adults in our society (this was particularly true in the past with certain cohorts, as college students tended to be mainly white males of high socioeconomic status). In fact, in the early research on aging, this type of convenience sample was compared with another type of convenience sample—young college students tended to be compared with residents of nursing homes! Fortunately, it didn’t take long for researchers to realize that older adults in nursing homes are not representative of the older population; they tend to be the oldest and sickest (physically and/or psychologically). Those initial studies probably painted an overly negative view of aging, as young adults in college were being compared to older adults who were not healthy, had not been in school nor taken tests in many decades, and probably did not graduate high school, let alone college. As we can see, recruitment and random sampling can be significant issues in research with adults, as well as infants and children. For instance, how and where would you recruit middle-aged adults to participate in your research?

A tired looking mother closes her eyes and rubs her forehead as her baby cries.

Another important consideration when conducting research with infants and young children is attrition . Although attrition is quite common in longitudinal research in particular (see the previous section on longitudinal designs for an example of high attrition rates and selective attrition in lifespan developmental research), it is also problematic in developmental science more generally, as studies with infants and young children tend to have higher attrition rates than studies with adults. Infants and young children are more likely to tire easily, become fussy, and lose interest in the study procedures than are adults. For these reasons, research studies should be designed to be as short as possible – it is likely better to break up a large study into multiple short sessions rather than cram all of the tasks into one long visit to the lab. Researchers should also allow time for breaks in their study protocols so that infants can rest or have snacks as needed. Happy, comfortable participants provide the best data.

Conclusions

Lifespan development is a fascinating field of study – but care must be taken to ensure that researchers use appropriate methods to examine human behavior, use the correct experimental design to answer their questions, and be aware of the special challenges that are part-and-parcel of developmental research. After reading this module, you should have a solid understanding of these various issues and be ready to think more critically about research questions that interest you. For example, what types of questions do you have about lifespan development? What types of research would you like to conduct? Many interesting questions remain to be examined by future generations of developmental scientists – maybe you will make one of the next big discoveries!

Lifespan development is the scientific study of how and why people change or remain the same over time. As we are beginning to see, lifespan development involves multiple domains and many ages and stages that are important in and of themselves, but that are also interdependent and dynamic and need to be viewed holistically. There are many influences on lifespan development at individual and societal levels (including genetics); cultural, generational, economic, and historical contexts are often significant. And how developmental research is designed and data are collected, analyzed, and interpreted can affect what is discovered about human development across the lifespan.

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Piaget’s Theory and Stages of Cognitive Development

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Key Takeaways

Jean Piaget is famous for his theories regarding changes in cognitive development that occur as we move from infancy to adulthood.
Cognitive development results from the interplay between innate capabilities (nature) and environmental influences (nurture).
Children progress through four distinct stages , each representing varying cognitive abilities and world comprehension: the sensorimotor stage (birth to 2 years), the preoperational stage (2 to 7 years), the concrete operational stage (7 to 11 years), and the formal operational stage (11 years and beyond).
A child’s cognitive development is not just about acquiring knowledge, the child has to develop or construct a mental model of the world, which is referred to as a schema .
Piaget emphasized the role of active exploration and interaction with the environment in shaping cognitive development, highlighting the importance of assimilation and accommodation in constructing mental schemas.

Stages of Development

Jean Piaget’s theory of cognitive development suggests that children move through four different stages of intellectual development which reflect the increasing sophistication of children’s thought

Each child goes through the stages in the same order (but not all at the same rate), and child development is determined by biological maturation and interaction with the environment.

At each stage of development, the child’s thinking is qualitatively different from the other stages, that is, each stage involves a different type of intelligence.

Although no stage can be missed out, there are individual differences in the rate at which children progress through stages, and some individuals may never attain the later stages.

Piaget did not claim that a particular stage was reached at a certain age – although descriptions of the stages often include an indication of the age at which the average child would reach each stage.

The Sensorimotor Stage

Ages: Birth to 2 Years

The first stage is the sensorimotor stage , during which the infant focuses on physical sensations and learning to coordinate its body.

Major Characteristics and Developmental Changes:

The infant learns about the world through their senses and through their actions (moving around and exploring their environment).
During the sensorimotor stage, a range of cognitive abilities develop. These include: object permanence; self-recognition (the child realizes that other people are separate from them); deferred imitation; and representational play.
They relate to the emergence of the general symbolic function, which is the capacity to represent the world mentally
At about 8 months, the infant will understand the permanence of objects and that they will still exist even if they can’t see them and the infant will search for them when they disappear.

During the beginning of this stage, the infant lives in the present. It does not yet have a mental picture of the world stored in its memory therefore it does not have a sense of object permanence.

If it cannot see something, then it does not exist. This is why you can hide a toy from an infant, while it watches, but it will not search for the object once it has gone out of sight.

The main achievement during this stage is object permanence – knowing that an object still exists, even if it is hidden. It requires the ability to form a mental representation (i.e., a schema) of the object.

Towards the end of this stage the general symbolic function begins to appear where children show in their play that they can use one object to stand for another. Language starts to appear because they realise that words can be used to represent objects and feelings.

The child begins to be able to store information that it knows about the world, recall it, and label it.

Individual Differences

Cultural Practices : In some cultures, babies are carried on their mothers’ backs throughout the day. This constant physical contact and varied stimuli can influence how a child perceives their environment and their sense of object permanence.
Gender Norms : Toys assigned to babies can differ based on gender expectations. A boy might be given more cars or action figures, while a girl might receive dolls or kitchen sets. This can influence early interactions and sensory explorations.

Learn More: The Sensorimotor Stage of Cognitive Development

The Preoperational Stage

Ages: 2 – 7 Years

Piaget’s second stage of intellectual development is the preoperational stage . It takes place between 2 and 7 years. At the beginning of this stage, the child does not use operations, so the thinking is influenced by the way things appear rather than logical reasoning.

A child cannot conserve which means that the child does not understand that quantity remains the same even if the appearance changes.

Furthermore, the child is egocentric; he assumes that other people see the world as he does. This has been shown in the three mountains study.

As the preoperational stage develops, egocentrism declines, and children begin to enjoy the participation of another child in their games, and let’s pretend play becomes more important.

Toddlers often pretend to be people they are not (e.g. superheroes, policemen), and may play these roles with props that symbolize real-life objects. Children may also invent an imaginary playmate.

Toddlers and young children acquire the ability to internally represent the world through language and mental imagery.
During this stage, young children can think about things symbolically. This is the ability to make one thing, such as a word or an object, stand for something other than itself.
A child’s thinking is dominated by how the world looks, not how the world is. It is not yet capable of logical (problem-solving) type of thought.
Moreover, the child has difficulties with class inclusion; he can classify objects but cannot include objects in sub-sets, which involves classifying objects as belonging to two or more categories simultaneously.
Infants at this stage also demonstrate animism. This is the tendency for the child to think that non-living objects (such as toys) have life and feelings like a person’s.

By 2 years, children have made some progress toward detaching their thoughts from the physical world. However, have not yet developed logical (or “operational”) thought characteristics of later stages.

Thinking is still intuitive (based on subjective judgments about situations) and egocentric (centered on the child’s own view of the world).

Cultural Storytelling : Different cultures have unique stories, myths, and folklore. Children from diverse backgrounds might understand and interpret symbolic elements differently based on their cultural narratives.
Race & Representation : A child’s racial identity can influence how they engage in pretend play. For instance, a lack of diverse representation in media and toys might lead children of color to recreate scenarios that don’t reflect their experiences or background.

Learn More: The Preoperational Stage of Cognitive Development

The Concrete Operational Stage

Ages: 7 – 11 Years

By the beginning of the concrete operational stage , the child can use operations (a set of logical rules) so they can conserve quantities, realize that people see the world in a different way (decentring), and demonstrate improvement in inclusion tasks. Children still have difficulties with abstract thinking.

During this stage, children begin to think logically about concrete events.
Children begin to understand the concept of conservation; understanding that, although things may change in appearance, certain properties remain the same.
During this stage, children can mentally reverse things (e.g., picture a ball of plasticine returning to its original shape).
During this stage, children also become less egocentric and begin to think about how other people might think and feel.

The stage is called concrete because children can think logically much more successfully if they can manipulate real (concrete) materials or pictures of them.

Piaget considered the concrete stage a major turning point in the child’s cognitive development because it marks the beginning of logical or operational thought. This means the child can work things out internally in their head (rather than physically try things out in the real world).

Children can conserve number (age 6), mass (age 7), and weight (age 9). Conservation is the understanding that something stays the same in quantity even though its appearance changes.

But operational thought is only effective here if the child is asked to reason about materials that are physically present. Children at this stage will tend to make mistakes or be overwhelmed when asked to reason about abstract or hypothetical problems.

Cultural Context in Conservation Tasks : In a society where resources are scarce, children might demonstrate conservation skills earlier due to the cultural emphasis on preserving and reusing materials.
Gender & Learning : Stereotypes about gender abilities, like “boys are better at math,” can influence how children approach logical problems or classify objects based on perceived gender norms.

Learn More: The Concrete Operational Stage of Development

The Formal Operational Stage

Ages: 12 and Over

The formal operational period begins at about age 11. As adolescents enter this stage, they gain the ability to think in an abstract manner, the ability to combine and classify items in a more sophisticated way, and the capacity for higher-order reasoning.

Adolescents can think systematically and reason about what might be as well as what is (not everyone achieves this stage). This allows them to understand politics, ethics, and science fiction, as well as to engage in scientific reasoning.

Adolescents can deal with abstract ideas: e.g. they can understand division and fractions without having to actually divide things up, and solve hypothetical (imaginary) problems.

Concrete operations are carried out on things whereas formal operations are carried out on ideas. Formal operational thought is entirely freed from physical and perceptual constraints.
During this stage, adolescents can deal with abstract ideas (e.g. no longer needing to think about slicing up cakes or sharing sweets to understand division and fractions).
They can follow the form of an argument without having to think in terms of specific examples.
Adolescents can deal with hypothetical problems with many possible solutions. E.g. if asked ‘What would happen if money were abolished in one hour’s time? they could speculate about many possible consequences.

From about 12 years children can follow the form of a logical argument without reference to its content. During this time, people develop the ability to think about abstract concepts, and logically test hypotheses.

This stage sees the emergence of scientific thinking, formulating abstract theories and hypotheses when faced with a problem.

Culture & Abstract Thinking : Cultures emphasize different kinds of logical or abstract thinking. For example, in societies with a strong oral tradition, the ability to hold complex narratives might develop prominently.
Gender & Ethics : Discussions about morality and ethics can be influenced by gender norms. For instance, in some cultures, girls might be encouraged to prioritize community harmony, while boys might be encouraged to prioritize individual rights.

Learn More: The Formal Operational Stage of Development

Piaget’s Theory

Piaget’s theory places a strong emphasis on the active role that children play in their own cognitive development.
According to Piaget, children are not passive recipients of information; instead, they actively explore and interact with their surroundings.
This active engagement with the environment is crucial because it allows them to gradually build their understanding of the world.

1. How Piaget Developed the Theory

Piaget was employed at the Binet Institute in the 1920s, where his job was to develop French versions of questions on English intelligence tests. He became intrigued with the reasons children gave for their wrong answers to the questions that required logical thinking.

He believed that these incorrect answers revealed important differences between the thinking of adults and children.

Piaget branched out on his own with a new set of assumptions about children’s intelligence:

Children’s intelligence differs from an adult’s in quality rather than in quantity. This means that children reason (think) differently from adults and see the world in different ways.
Children actively build up their knowledge about the world . They are not passive creatures waiting for someone to fill their heads with knowledge.
The best way to understand children’s reasoning is to see things from their point of view.

Piaget did not want to measure how well children could count, spell or solve problems as a way of grading their I.Q. What he was more interested in was the way in which fundamental concepts like the very idea of number , time, quantity, causality , justice , and so on emerged.

Piaget studied children from infancy to adolescence using naturalistic observation of his own three babies and sometimes controlled observation too. From these, he wrote diary descriptions charting their development.

He also used clinical interviews and observations of older children who were able to understand questions and hold conversations.

2. Piaget’s Theory Differs From Others In Several Ways:

Piaget’s (1936, 1950) theory of cognitive development explains how a child constructs a mental model of the world. He disagreed with the idea that intelligence was a fixed trait, and regarded cognitive development as a process that occurs due to biological maturation and interaction with the environment.

Children’s ability to understand, think about, and solve problems in the world develops in a stop-start, discontinuous manner (rather than gradual changes over time).

It is concerned with children, rather than all learners.
It focuses on development, rather than learning per se, so it does not address learning of information or specific behaviors.
It proposes discrete stages of development, marked by qualitative differences, rather than a gradual increase in number and complexity of behaviors, concepts, ideas, etc.

The goal of the theory is to explain the mechanisms and processes by which the infant, and then the child, develops into an individual who can reason and think using hypotheses.

To Piaget, cognitive development was a progressive reorganization of mental processes as a result of biological maturation and environmental experience.

Children construct an understanding of the world around them, then experience discrepancies between what they already know and what they discover in their environment.

Piaget claimed that knowledge cannot simply emerge from sensory experience; some initial structure is necessary to make sense of the world.

According to Piaget, children are born with a very basic mental structure (genetically inherited and evolved) on which all subsequent learning and knowledge are based.

Schemas are the basic building blocks of such cognitive models, and enable us to form a mental representation of the world.

Piaget (1952, p. 7) defined a schema as: “a cohesive, repeatable action sequence possessing component actions that are tightly interconnected and governed by a core meaning.”

In more simple terms, Piaget called the schema the basic building block of intelligent behavior – a way of organizing knowledge. Indeed, it is useful to think of schemas as “units” of knowledge, each relating to one aspect of the world, including objects, actions, and abstract (i.e., theoretical) concepts.

Wadsworth (2004) suggests that schemata (the plural of schema) be thought of as “index cards” filed in the brain, each one telling an individual how to react to incoming stimuli or information.

When Piaget talked about the development of a person’s mental processes, he was referring to increases in the number and complexity of the schemata that a person had learned.

When a child’s existing schemas are capable of explaining what it can perceive around it, it is said to be in a state of equilibrium, i.e., a state of cognitive (i.e., mental) balance.

Operations are more sophisticated mental structures which allow us to combine schemas in a logical (reasonable) way.

As children grow they can carry out more complex operations and begin to imagine hypothetical (imaginary) situations.

Apart from the schemas we are born with schemas and operations are learned through interaction with other people and the environment.

Piaget emphasized the importance of schemas in cognitive development and described how they were developed or acquired.

A schema can be defined as a set of linked mental representations of the world, which we use both to understand and to respond to situations. The assumption is that we store these mental representations and apply them when needed.

Examples of Schemas

A person might have a schema about buying a meal in a restaurant. The schema is a stored form of the pattern of behavior which includes looking at a menu, ordering food, eating it and paying the bill.

This is an example of a schema called a “script.” Whenever they are in a restaurant, they retrieve this schema from memory and apply it to the situation.

The schemas Piaget described tend to be simpler than this – especially those used by infants. He described how – as a child gets older – his or her schemas become more numerous and elaborate.

Piaget believed that newborn babies have a small number of innate schemas – even before they have had many opportunities to experience the world. These neonatal schemas are the cognitive structures underlying innate reflexes. These reflexes are genetically programmed into us.

For example, babies have a sucking reflex, which is triggered by something touching the baby’s lips. A baby will suck a nipple, a comforter (dummy), or a person’s finger. Piaget, therefore, assumed that the baby has a “sucking schema.”

Similarly, the grasping reflex which is elicited when something touches the palm of a baby’s hand, or the rooting reflex, in which a baby will turn its head towards something which touches its cheek, are innate schemas. Shaking a rattle would be the combination of two schemas, grasping and shaking.

4. The Process of Adaptation

Piaget also believed that a child developed as a result of two different influences: maturation, and interaction with the environment. The child develops mental structures (schemata) which enables him to solve problems in the environment.

Adaptation is the process by which the child changes its mental models of the world to match more closely how the world actually is.

Adaptation is brought about by the processes of assimilation (solving new experiences using existing schemata) and accommodation (changing existing schemata in order to solve new experiences).

The importance of this viewpoint is that the child is seen as an active participant in its own development rather than a passive recipient of either biological influences (maturation) or environmental stimulation.

When our existing schemas can explain what we perceive around us, we are in a state of equilibration . However, when we meet a new situation that we cannot explain it creates disequilibrium, this is an unpleasant sensation which we try to escape, and this gives us the motivation to learn.

According to Piaget, reorganization to higher levels of thinking is not accomplished easily. The child must “rethink” his or her view of the world. An important step in the process is the experience of cognitive conflict.

In other words, the child becomes aware that he or she holds two contradictory views about a situation and they both cannot be true. This step is referred to as disequilibrium .

Jean Piaget (1952; see also Wadsworth, 2004) viewed intellectual growth as a process of adaptation (adjustment) to the world. This happens through assimilation, accommodation, and equilibration.

To get back to a state of equilibration, we need to modify our existing schemas to learn and adapt to the new situation.

This is done through the processes of accommodation and assimilation . This is how our schemas evolve and become more sophisticated. The processes of assimilation and accommodation are continuous and interactive.

5. Assimilation

Piaget defined assimilation as the cognitive process of fitting new information into existing cognitive schemas, perceptions, and understanding. Overall beliefs and understanding of the world do not change as a result of the new information.

Assimilation occurs when the new experience is not very different from previous experiences of a particular object or situation we assimilate the new situation by adding information to a previous schema.

This means that when you are faced with new information, you make sense of this information by referring to information you already have (information processed and learned previously) and trying to fit the new information into the information you already have.

Imagine a young child who has only ever seen small, domesticated dogs. When the child sees a cat for the first time, they might refer to it as a “dog” because it has four legs, fur, and a tail – features that fit their existing schema of a dog.
A person who has always believed that all birds can fly might label penguins as birds that can fly. This is because their existing schema or understanding of birds includes the ability to fly.
A 2-year-old child sees a man who is bald on top of his head and has long frizzy hair on the sides. To his father’s horror, the toddler shouts “Clown, clown” (Siegler et al., 2003).
If a baby learns to pick up a rattle he or she will then use the same schema (grasping) to pick up other objects.

6. Accommodation

Accommodation: when the new experience is very different from what we have encountered before we need to change our schemas in a very radical way or create a whole new schema.

Psychologist Jean Piaget defined accommodation as the cognitive process of revising existing cognitive schemas, perceptions, and understanding so that new information can be incorporated.

This happens when the existing schema (knowledge) does not work, and needs to be changed to deal with a new object or situation.

In order to make sense of some new information, you actually adjust information you already have (schemas you already have, etc.) to make room for this new information.

A baby tries to use the same schema for grasping to pick up a very small object. It doesn’t work. The baby then changes the schema by now using the forefinger and thumb to pick up the object.
A child may have a schema for birds (feathers, flying, etc.) and then they see a plane, which also flies, but would not fit into their bird schema.
In the “clown” incident, the boy’s father explained to his son that the man was not a clown and that even though his hair was like a clown’s, he wasn’t wearing a funny costume and wasn’t doing silly things to make people laugh. With this new knowledge, the boy was able to change his schema of “clown” and make this idea fit better to a standard concept of “clown”.
A person who grew up thinking all snakes are dangerous might move to an area where garden snakes are common and harmless. Over time, after observing and learning, they might accommodate their previous belief to understand that not all snakes are harmful.

7. Equilibration

Piaget believed that all human thought seeks order and is uncomfortable with contradictions and inconsistencies in knowledge structures. In other words, we seek “equilibrium” in our cognitive structures.

Equilibrium occurs when a child’s schemas can deal with most new information through assimilation. However, an unpleasant state of disequilibrium occurs when new information cannot be fitted into existing schemas (assimilation).

Piaget believed that cognitive development did not progress at a steady rate, but rather in leaps and bounds. Equilibration is the force which drives the learning process as we do not like to be frustrated and will seek to restore balance by mastering the new challenge (accommodation).

Once the new information is acquired the process of assimilation with the new schema will continue until the next time we need to make an adjustment to it.

Equilibration is a regulatory process that maintains a balance between assimilation and accommodation to facilitate cognitive growth. Think of it this way: We can’t merely assimilate all the time; if we did, we would never learn any new concepts or principles.

Everything new we encountered would just get put in the same few “slots” we already had. Neither can we accommodate all the time; if we did, everything we encountered would seem new; there would be no recurring regularities in our world. We’d be exhausted by the mental effort!

Applications to Education

Think of old black and white films that you’ve seen in which children sat in rows at desks, with ink wells, would learn by rote, all chanting in unison in response to questions set by an authoritarian old biddy like Matilda!

Children who were unable to keep up were seen as slacking and would be punished by variations on the theme of corporal punishment. Yes, it really did happen and in some parts of the world still does today.

Piaget is partly responsible for the change that occurred in the 1960s and for your relatively pleasurable and pain-free school days!

“Children should be able to do their own experimenting and their own research. Teachers, of course, can guide them by providing appropriate materials, but the essential thing is that in order for a child to understand something, he must construct it himself, he must re-invent it. Every time we teach a child something, we keep him from inventing it himself. On the other hand that which we allow him to discover by himself will remain with him visibly”. Piaget (1972, p. 27)

Plowden Report

Piaget (1952) did not explicitly relate his theory to education, although later researchers have explained how features of Piaget’s theory can be applied to teaching and learning.

Piaget has been extremely influential in developing educational policy and teaching practice. For example, a review of primary education by the UK government in 1966 was based strongly on Piaget’s theory. The result of this review led to the publication of the Plowden Report (1967).

In the 1960s the Plowden Committee investigated the deficiencies in education and decided to incorporate many of Piaget’s ideas into its final report published in 1967, even though Piaget’s work was not really designed for education.

The report makes three Piaget-associated recommendations:

Children should be given individual attention and it should be realized that they need to be treated differently.
Children should only be taught things that they are capable of learning
Children mature at different rates and the teacher needs to be aware of the stage of development of each child so teaching can be tailored to their individual needs.

“The report’s recurring themes are individual learning, flexibility in the curriculum, the centrality of play in children’s learning, the use of the environment, learning by discovery and the importance of the evaluation of children’s progress – teachers should “not assume that only what is measurable is valuable.”

Discovery learning – the idea that children learn best through doing and actively exploring – was seen as central to the transformation of the primary school curriculum.

How to teach

Within the classroom learning should be student-centered and accomplished through active discovery learning. The role of the teacher is to facilitate learning, rather than direct tuition.

Because Piaget’s theory is based upon biological maturation and stages, the notion of “readiness” is important. Readiness concerns when certain information or concepts should be taught.

According to Piaget’s theory, children should not be taught certain concepts until they have reached the appropriate stage of cognitive development.

According to Piaget (1958), assimilation and accommodation require an active learner, not a passive one, because problem-solving skills cannot be taught, they must be discovered.

Therefore, teachers should encourage the following within the classroom:

Educational programs should be designed to correspond to Piaget’s stages of development. Children in the concrete operational stage should be given concrete means to learn new concepts e.g. tokens for counting.
Devising situations that present useful problems, and create disequilibrium in the child.
Focus on the process of learning, rather than the end product of it. Instead of checking if children have the right answer, the teacher should focus on the student’s understanding and the processes they used to get to the answer.
Child-centered approach. Learning must be active (discovery learning). Children should be encouraged to discover for themselves and to interact with the material instead of being given ready-made knowledge.
Accepting that children develop at different rates so arrange activities for individual children or small groups rather than assume that all the children can cope with a particular activity.
Using active methods that require rediscovering or reconstructing “truths.”
Using collaborative, as well as individual activities (so children can learn from each other).
Evaluate the level of the child’s development so suitable tasks can be set.
Adapt lessons to suit the needs of the individual child (i.e. differentiated teaching).
Be aware of the child’s stage of development (testing).
Teach only when the child is ready. i.e. has the child reached the appropriate stage.
Providing support for the “spontaneous research” of the child.
Using collaborative, as well as individual activities.
Educators may use Piaget’s stages to design age-appropriate assessment tools and strategies.

Classroom Activities

Sensorimotor stage (0-2 years):.

Although most kids in this age range are not in a traditional classroom setting, they can still benefit from games that stimulate their senses and motor skills.

Object Permanence Games : Play peek-a-boo or hide toys under a blanket to help babies understand that objects still exist even when they can’t see them.
Sensory Play : Activities like water play, sand play, or playdough encourage exploration through touch.
Imitation : Children at this age love to imitate adults. Use imitation as a way to teach new skills.

Preoperational Stage (2-7 years):

Role Playing : Set up pretend play areas where children can act out different scenarios, such as a kitchen, hospital, or market.
Use of Symbols : Encourage drawing, building, and using props to represent other things.
Hands-on Activities : Children should interact physically with their environment, so provide plenty of opportunities for hands-on learning.
Egocentrism Activities : Use exercises that highlight different perspectives. For instance, having two children sit across from each other with an object in between and asking them what the other sees.

Concrete Operational Stage (7-11 years):

Classification Tasks : Provide objects or pictures to group, based on various characteristics.
Hands-on Experiments : Introduce basic science experiments where they can observe cause and effect, like a simple volcano with baking soda and vinegar.
Logical Games : Board games, puzzles, and logic problems help develop their thinking skills.
Conservation Tasks : Use experiments to showcase that quantity doesn’t change with alterations in shape, such as the classic liquid conservation task using different shaped glasses.

Formal Operational Stage (11 years and older):

Hypothesis Testing : Encourage students to make predictions and test them out.
Abstract Thinking : Introduce topics that require abstract reasoning, such as algebra or ethical dilemmas.
Problem Solving : Provide complex problems and have students work on solutions, integrating various subjects and concepts.
Debate and Discussion : Encourage group discussions and debates on abstract topics, highlighting the importance of logic and evidence.
Feedback and Questioning : Use open-ended questions to challenge students and promote higher-order thinking. For instance, rather than asking, “Is this the right answer?”, ask, “How did you arrive at this conclusion?”

While Piaget’s stages offer a foundational framework, they are not universally experienced in the same way by all children.

Social identities play a critical role in shaping cognitive development, necessitating a more nuanced and culturally responsive approach to understanding child development.

Piaget’s stages may manifest differently based on social identities like race, gender, and culture:

Race & Teacher Interactions : A child’s race can influence teacher expectations and interactions. For example, racial biases can lead to children of color being perceived as less capable or more disruptive, influencing their cognitive challenges and supports.
Racial and Cultural Stereotypes : These can affect a child’s self-perception and self-efficacy . For instance, stereotypes about which racial or cultural groups are “better” at certain subjects can influence a child’s self-confidence and, subsequently, their engagement in that subject.
Gender & Peer Interactions : Children learn gender roles from their peers. Boys might be mocked for playing “girl games,” and girls might be excluded from certain activities, influencing their cognitive engagements.
Language : Multilingual children might navigate the stages differently, especially if their home language differs from their school language. The way concepts are framed in different languages can influence cognitive processing. Cultural idioms and metaphors can shape a child’s understanding of concepts and their ability to use symbolic representation, especially in the pre-operational stage.

Curriculum Development

According to Piaget, children’s cognitive development is determined by a process of maturation which cannot be altered by tuition so education should be stage-specific.

For example, a child in the concrete operational stage should not be taught abstract concepts and should be given concrete aid such as tokens to count with.

According to Piaget children learn through the process of accommodation and assimilation so the role of the teacher should be to provide opportunities for these processes to occur such as new material and experiences that challenge the children’s existing schemas.

Furthermore, according to this theory, children should be encouraged to discover for themselves and to interact with the material instead of being given ready-made knowledge.

Curricula need to be developed that take into account the age and stage of thinking of the child. For example there is no point in teaching abstract concepts such as algebra or atomic structure to children in primary school.

Curricula also need to be sufficiently flexible to allow for variations in the ability of different students of the same age. In Britain, the National Curriculum and Key Stages broadly reflect the stages that Piaget laid down.

For example, egocentrism dominates a child’s thinking in the sensorimotor and preoperational stages. Piaget would therefore predict that using group activities would not be appropriate since children are not capable of understanding the views of others.

However, Smith et al. (1998), point out that some children develop earlier than Piaget predicted and that by using group work children can learn to appreciate the views of others in preparation for the concrete operational stage.

The national curriculum emphasizes the need to use concrete examples in the primary classroom.

Shayer (1997), reported that abstract thought was necessary for success in secondary school (and co-developed the CASE system of teaching science). Recently the National curriculum has been updated to encourage the teaching of some abstract concepts towards the end of primary education, in preparation for secondary courses. (DfEE, 1999).

Child-centered teaching is regarded by some as a child of the ‘liberal sixties.’ In the 1980s the Thatcher government introduced the National Curriculum in an attempt to move away from this and bring more central government control into the teaching of children.

So, although the British National Curriculum in some ways supports the work of Piaget, (in that it dictates the order of teaching), it can also be seen as prescriptive to the point where it counters Piaget’s child-oriented approach.

However, it does still allow for flexibility in teaching methods, allowing teachers to tailor lessons to the needs of their students.

Social Media (Digital Learning)

Jean Piaget could not have anticipated the expansive digital age we now live in.

Today, knowledge dissemination and creation are democratized by the Internet, with platforms like blogs, wikis, and social media allowing for vast collaboration and shared knowledge. This development has prompted a reimagining of the future of education.

Classrooms, traditionally seen as primary sites of learning, are being overshadowed by the rise of mobile technologies and platforms like MOOCs (Passey, 2013).

The millennial generation, defined as the first to grow up with cable TV, the internet, and cell phones, relies heavily on technology.

They view it as an integral part of their identity, with most using it extensively in their daily lives, from keeping in touch with loved ones to consuming news and entertainment (Nielsen, 2014).

Social media platforms offer a dynamic environment conducive to Piaget’s principles. These platforms allow for interactions that nurture knowledge evolution through cognitive processes like assimilation and accommodation.

They emphasize communal interaction and shared activity, fostering both cognitive and socio-cultural constructivism. This shared activity promotes understanding and exploration beyond individual perspectives, enhancing social-emotional learning (Gehlbach, 2010).

A standout advantage of social media in an educational context is its capacity to extend beyond traditional classroom confines. As the material indicates, these platforms can foster more inclusive learning, bridging diverse learner groups.

This inclusivity can equalize learning opportunities, potentially diminishing biases based on factors like race or socio-economic status, resonating with Kegan’s (1982) concept of “recruitability.”

However, there are challenges. While the potential of social media in learning is vast, its practical application necessitates intention and guidance. Cuban, Kirkpatrick, and Peck (2001) note that certain educators and students are hesitant about integrating social media into educational contexts.

This hesitancy can stem from technological complexities or potential distractions. Yet, when harnessed effectively, social media can provide a rich environment for collaborative learning and interpersonal development, fostering a deeper understanding of content.

In essence, the rise of social media aligns seamlessly with constructivist philosophies. Social media platforms act as tools for everyday cognition, merging daily social interactions with the academic world, and providing avenues for diverse, interactive, and engaging learning experiences.

Applications to Parenting

Parents can use Piaget’s stages to have realistic developmental expectations of their children’s behavior and cognitive capabilities.

For instance, understanding that a toddler is in the pre-operational stage can help parents be patient when the child is egocentric.

Play Activities

Recognizing the importance of play in cognitive development, many parents provide toys and games suited for their child’s developmental stage.

Parents can offer activities that are slightly beyond their child’s current abilities, leveraging Vygotsky’s concept of the “Zone of Proximal Development,” which complements Piaget’s ideas.

Peek-a-boo : Helps with object permanence.
Texture Touch : Provide different textured materials (soft, rough, bumpy, smooth) for babies to touch and feel.
Sound Bottles : Fill small bottles with different items like rice, beans, bells, and have children shake and listen to the different sounds.
Memory Games : Using cards with pictures, place them face down, and ask students to find matching pairs.
Role Playing and Pretend Play : Let children act out roles or stories that enhance symbolic thinking. Encourage symbolic play with dress-up clothes, playsets, or toy cash registers. Provide prompts or scenarios to extend their imagination.
Story Sequencing : Give children cards with parts of a story and have them arranged in the correct order.
Number Line Jumps : Create a number line on the floor with tape. Ask students to jump to the correct answer for math problems.
Classification Games : Provide a mix of objects and ask students to classify them based on different criteria (e.g., color, size, shape).
Logical Puzzle Games : Games that involve problem-solving using logic, such as simple Sudoku puzzles or logic grid puzzles.
Debate and Discussion : Provide a topic and let students debate on pros and cons. This promotes abstract thinking and logical reasoning.
Hypothesis Testing Games : Present a scenario and have students come up with hypotheses and ways to test them.
Strategy Board Games : Games like chess, checkers, or Settlers of Catan can help in developing strategic and forward-thinking skills.

Critical Evaluation

The influence of Piaget’s ideas on developmental psychology has been enormous. He changed how people viewed the child’s world and their methods of studying children.

He was an inspiration to many who came after and took up his ideas. Piaget’s ideas have generated a huge amount of research which has increased our understanding of cognitive development.

Piaget (1936) was one of the first psychologists to make a systematic study of cognitive development. His contributions include a stage theory of child cognitive development, detailed observational studies of cognition in children, and a series of simple but ingenious tests to reveal different cognitive abilities.
His ideas have been of practical use in understanding and communicating with children, particularly in the field of education (re: Discovery Learning). Piaget’s theory has been applied across education.
According to Piaget’s theory, educational programs should be designed to correspond to the stages of development.
Are the stages real? Vygotsky and Bruner would rather not talk about stages at all, preferring to see development as a continuous process. Others have queried the age ranges of the stages. Some studies have shown that progress to the formal operational stage is not guaranteed.

For example, Keating (1979) reported that 40-60% of college students fail at formal operation tasks, and Dasen (1994) states that only one-third of adults ever reach the formal operational stage.

The fact that the formal operational stage is not reached in all cultures and not all individuals within cultures suggests that it might not be biologically based.

According to Piaget, the rate of cognitive development cannot be accelerated as it is based on biological processes however, direct tuition can speed up the development which suggests that it is not entirely based on biological factors.
Because Piaget concentrated on the universal stages of cognitive development and biological maturation, he failed to consider the effect that the social setting and culture may have on cognitive development.

Cross-cultural studies show that the stages of development (except the formal operational stage) occur in the same order in all cultures suggesting that cognitive development is a product of a biological process of maturation.

However, the age at which the stages are reached varies between cultures and individuals which suggests that social and cultural factors and individual differences influence cognitive development.

Dasen (1994) cites studies he conducted in remote parts of the central Australian desert with 8-14-year-old Indigenous Australians. He gave them conservation of liquid tasks and spatial awareness tasks. He found that the ability to conserve came later in the Aboriginal children, between ages of 10 and 13 (as opposed to between 5 and 7, with Piaget’s Swiss sample).

However, he found that spatial awareness abilities developed earlier amongst the Aboriginal children than the Swiss children. Such a study demonstrates cognitive development is not purely dependent on maturation but on cultural factors too – spatial awareness is crucial for nomadic groups of people.

Vygotsky , a contemporary of Piaget, argued that social interaction is crucial for cognitive development. According to Vygotsky the child’s learning always occurs in a social context in cooperation with someone more skillful (MKO). This social interaction provides language opportunities and Vygotsky considered language the foundation of thought.

Piaget’s methods (observation and clinical interviews) are more open to biased interpretation than other methods. Piaget made careful, detailed naturalistic observations of children, and from these, he wrote diary descriptions charting their development. He also used clinical interviews and observations of older children who were able to understand questions and hold conversations.

Because Piaget conducted the observations alone the data collected are based on his own subjective interpretation of events. It would have been more reliable if Piaget conducted the observations with another researcher and compared the results afterward to check if they are similar (i.e., have inter-rater reliability).

Although clinical interviews allow the researcher to explore data in more depth, the interpretation of the interviewer may be biased.

For example, children may not understand the question/s, they have short attention spans, they cannot express themselves very well, and may be trying to please the experimenter. Such methods meant that Piaget may have formed inaccurate conclusions.

As several studies have shown Piaget underestimated the abilities of children because his tests were sometimes confusing or difficult to understand (e.g., Hughes , 1975).

Piaget failed to distinguish between competence (what a child is capable of doing) and performance (what a child can show when given a particular task). When tasks were altered, performance (and therefore competence) was affected. Therefore, Piaget might have underestimated children’s cognitive abilities.

For example, a child might have object permanence (competence) but still not be able to search for objects (performance). When Piaget hid objects from babies he found that it wasn’t till after nine months that they looked for it.

However, Piaget relied on manual search methods – whether the child was looking for the object or not.

Later, researchers such as Baillargeon and Devos (1991) reported that infants as young as four months looked longer at a moving carrot that didn’t do what it expected, suggesting they had some sense of permanence, otherwise they wouldn’t have had any expectation of what it should or shouldn’t do.

The concept of schema is incompatible with the theories of Bruner (1966) and Vygotsky (1978). Behaviorism would also refute Piaget’s schema theory because is cannot be directly observed as it is an internal process. Therefore, they would claim it cannot be objectively measured.
Piaget studied his own children and the children of his colleagues in Geneva to deduce general principles about the intellectual development of all children. His sample was very small and composed solely of European children from families of high socio-economic status. Researchers have, therefore, questioned the generalisability of his data.
For Piaget, language is considered secondary to action, i.e., thought precedes language. The Russian psychologist Lev Vygotsky (1978) argues that the development of language and thought go together and that the origin of reasoning has more to do with our ability to communicate with others than with our interaction with the material world.

Piaget’s Theory vs Vygotsky

Piaget maintains that cognitive development stems largely from independent explorations in which children construct knowledge of their own.

Whereas Vygotsky argues that children learn through social interactions, building knowledge by learning from more knowledgeable others such as peers and adults. In other words, Vygotsky believed that culture affects cognitive development.

These factors lead to differences in the education style they recommend: Piaget would argue for the teacher to provide opportunities that challenge the children’s existing schemas and for children to be encouraged to discover for themselves.

Alternatively, Vygotsky would recommend that teachers assist the child to progress through the zone of proximal development by using scaffolding.

However, both theories view children as actively constructing their own knowledge of the world; they are not seen as just passively absorbing knowledge.

They also agree that cognitive development involves qualitative changes in thinking, not only a matter of learning more things.

What is cognitive development?

Cognitive development is how a person’s ability to think, learn, remember, problem-solve, and make decisions changes over time.

This includes the growth and maturation of the brain, as well as the acquisition and refinement of various mental skills and abilities.

Cognitive development is a major aspect of human development, and both genetic and environmental factors heavily influence it. Key domains of cognitive development include attention, memory, language skills, logical reasoning, and problem-solving.

Various theories, such as those proposed by Jean Piaget and Lev Vygotsky, provide different perspectives on how this complex process unfolds from infancy through adulthood.

What are the 4 stages of Piaget’s theory?

Piaget divided children’s cognitive development into four stages; each of the stages represents a new way of thinking and understanding the world.

He called them (1) sensorimotor intelligence , (2) preoperational thinking , (3) concrete operational thinking , and (4) formal operational thinking . Each stage is correlated with an age period of childhood, but only approximately.

According to Piaget, intellectual development takes place through stages that occur in a fixed order and which are universal (all children pass through these stages regardless of social or cultural background).

Development can only occur when the brain has matured to a point of “readiness”.

What are some of the weaknesses of Piaget’s theory?

However, the age at which the stages are reached varies between cultures and individuals, suggesting that social and cultural factors and individual differences influence cognitive development.

What are Piaget’s concepts of schemas?

Schemas are mental structures that contain all of the information relating to one aspect of the world around us.

According to Piaget, we are born with a few primitive schemas, such as sucking, which give us the means to interact with the world.

These are physical, but as the child develops, they become mental schemas. These schemas become more complex with experience.

Baillargeon, R., & DeVos, J. (1991). Object permanence in young infants: Further evidence . Child development , 1227-1246.

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Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High access and low use of technologies in high school classrooms: Explaining an apparent paradox. American Educational Research Journal , 38 (4), 813-834.

Dasen, P. (1994). Culture and cognitive development from a Piagetian perspective. In W .J. Lonner & R.S. Malpass (Eds.), Psychology and culture (pp. 145–149). Boston, MA: Allyn and Bacon.

Gehlbach, H. (2010). The social side of school: Why teachers need social psychology. Educational Psychology Review , 22 , 349-362.

Hughes, M. (1975). Egocentrism in preschool children . Unpublished doctoral dissertation. Edinburgh University.

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Keating, D. (1979). Adolescent thinking. In J. Adelson (Ed.), Handbook of adolescent psychology (pp. 211-246). New York: Wiley.

Kegan, R. (1982). The evolving self: Problem and process in human development . Harvard University Press.

Nielsen. 2014. “Millennials: Technology = Social Connection.” http://www.nielsen.com/content/corporate/us/en/insights/news/2014/millennials-technology-social-connecti on.html.

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Siegler, R. S., DeLoache, J. S., & Eisenberg, N. (2003). How children develop . New York: Worth.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes . Cambridge, MA: Harvard University Press.

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Developing a Researchable Hypothesis

Your research project should build on a well-defined and well-studied area of research. Developing and focusing your research hypothesis will make putting together your research proposal and project much easier.

Do some exploratory research on your broad research idea in your course textbook, class notes, and PsycINFO to identify more specific issues and arguments in your research area and possible relationships between them. You should also identify the methodologies and tests that are used to study your research area, as well as the populations that are studied.

Ask yourself questions about your research topic : What interests me about this topic? What have people said about it? What gaps, contradictions, or concerns arise as you learn more about it? What relationships are there between different aspects of the topic?

Write a research question that your hypothesis answers : Use the information from your exploratory research and your answers to questions about your broad topic and the area you've decided to explore to build a focused, clear, simple research question

Identify the key concepts of your research question : what concepts will you need to define and measure in a study to answer your research question? How will you operationally define these concepts into numbers that you can analyze?

Identify your variables: Use your operational definitions to identify and list the independent and dependent variables for your research question. Identify possible confounding variables and the variables you would use to control for them.

Choose a current topic: Develop a hypothesis for a research area about which articles are continuing to be published. Avoid defunct or little-known areas of research.

Write about what interests you: Professors want students to develop experiments in areas that they care about. If you're interested in the topic, it will be more fun for you to do your experiment and write up your research paper, and probably more fun for your professor to read it, too.

Ask your professor for feedback on whether the hypothesis you develop is a good hypothesis, one that can be tested.

Picking Your Topic IS Research

Once you've picked a research topic for your paper, it isn't set in stone. It's just an idea that you will test and develop through exploratory research. This exploratory research may guide you into modifying your original idea for a research topic. Watch this video for more info:

<< Previous: Identify Research Gaps
Next: Identify/Justify Methods & Populations >>
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Define Hypothesis: Unveiling the First Step in Scientific Inquiry

Master Scientific Data Visualization. Learn how to make data easier, unlock insights and captivate audiences effectively.

Welcome to the world of research, where you’ll journey through a universe brimming with questions and curiosity. In this cosmos, a hypothesis is one celestial object you can’t miss! Today’s expedition invites you on board an exploration to ‘Define Hypothesis.’ Hop in; it wouldn’t be hyperbole to state we’re about to unlock the nucleus behind every ever scientific theory and inquiry!

Definition of Hypothesis

Introduction to the concept of hypothesis.

Picture yourself as a detective solving a case. Right from inspecting clues, formulating potential theories on whodunit, putting these theories under rigorous tests until finally reaching that elusive conclusive evidence – exciting, isn’t it?

Now replace detective with researcher and voila – here comes our heavyweight term: Hypothesis. Much like how any plausible theory drives detectives’ investigations, scientific hypotheses are vital navigational compasses guiding researchers in their quest for scientific evolutions.

Explanation of What a Hypothesis Is in The Context of Research and Scientific Inquiry

A hypothesis – popularly known as an educated guess or predictive statement – represents an initial supposition or proposed explanation made on limited information but founded on validation-grounded knowledge. It forms the basis for preliminary exploration into a specific set of circumstances or natural phenomena beyond.

Formulated prior to conducting research, scientists employ hypotheses as testable conjectures to explain an observed behavior or event. Confused? Fret not. To put it simply and by example: “If I increase the frequency of watering my plants twice daily (instead of solely relying upon weather conditions), then they will grow faster.” Now that’s what we call an everyday-life hypothesis!

Remember, hypotheses are not wild guesses plucked out of thin air but rather preconceived assertions open to empirical verification. They mark the inception point for any scientific investigation and serve as cornerstones for further experiments.

Characteristics and Components of a Hypothesis

Key characteristics of a hypothesis.

Before plunging into the deep end to define a hypothesis, let’s brush up on the features that contribute to effective hypotheses. For starters, a strong hypothesis is testable. This means it must be possible for empirical evidence to either support the word hypothesis or contradict it. The proposal should also be logically consistent and grounded firmly in existing knowledge.

Further down the line, another salient feature is specificity. Good hypotheses are not broad statements but instead focus on a specific aspect or phenomenon within the intended research field. Moreover, they are typically succinct and easily understandable ensuring information isn’t lost in translation among researchers.

Moreover, any well-structured hypothesis connects the independent and dependent variables together – typically, there’s at least one independent and one dependent variable involved. These elements form a relationship where changes instigated in the independent variable affect the values observed for the dependent variable.

Lastly but importantly, a solid hypothesis often carries potential implications for future research areas and can potentially lead to further tests and studies if verified.

Elements that make up a well-formulated hypothesis

Delving deeper into what shapes up a robust hypothesis, we realize that certain crucial components determine its effectiveness.

Firstly, every good hypothesis or test has clear variables which essentially refer to specific aspects of the study subject matter being measured or manipulated during research. These aspects are segregated as:

Independent Variable (IV): This component relates directly to what you have control over in your study.
Dependent Variable (DV): This component consists of outcomes affected by alterations made in IV

Next comes ‘Predicted Outcome’ – what you anticipate happening as repercussions due to modification of two or more variables under scrutiny.

The ‘Testability’ factor also holds veritable importance comprising experimental procedures capable enough to refute or accept your claims.

The last element circles the argument around presenting a capacity called ‘Relationship’ correlating IV with DV believed to either causing some effect or showcasing an association.

Hence, these prime facets further accentuate your endeavor to adequately define the hypothesis.

Importance and Purpose of a Hypothesis

Understanding the Role of a Hypothesis in Research

First, let’s delve into the overarching role that hypothesis plays within research scenarios. As we define the hypothesis, you should view this as an underlying pillar or guiding star for your investigation. A well-articulated hypothesis steers your exploration by providing clarity on what specifically you aim to examine.

A meaningful analogy would be considering a hypothesis as a compass during a voyage. If research is the vast ocean where confusing whirlpools of data and evidence abound, then it can guide us in our direction rather than letting us drift aimlessly. Furthermore, the formulation of a quality hypothesis inherently demands clarity about your objectives upfront – this essentially sets your research vessel on course bearing towards effective outcomes.

Exploring Why Formulating A Hypothesis is Crucial in Scientific Investigations

So why precisely is nurturing such a detailed forecast vital?

Structural Advantage: By proposing potential answers to posed questions via hypotheses, researchers streamline their methods and techniques. The approach undertaken depends significantly on what the suggested outcome or phenomenon might be.
Generate Preliminary Expectations: Even if they’re proven wrong, making observations and developing models based on hypotheses often lead to more interesting inquiries or turn up unexpected findings.
Quantifiable Predictions: More than simple conjectures, strong hypotheses are testable; they propose results expressed in measurable terms.

In essence, remember that formulating hypotheses smoothes the path towards solid conclusions by being the architect’s blueprints of robust investigations. Never underestimate the forward thrust they provide for progress within scientific inquiry!

Types of Hypotheses

Once we understand to define a hypothesis, we’ll find that hypotheses come in several types. Different classifications of plural hypotheses depend on their formulations and the nature of predictions or assumptions they lead towards – simple, complex, directional, non-directional, null, associative and causal. Let’s explore some of these.

Simple Hypothesis: Definition and Examples

A simple hypothesis is a type of prediction or an educated guess that carries one independent variable and one dependent variable. In essence, it creates a relationship between two singular entities; for instance, ‘Exercise improves memory.’ This suggests that there’s an impact (of improvement) on the ‘memory’ (dependent variable) by ‘exercise’ (independent variable).

Complex Hypothesis: Definition and Examples

On the contrary to its name mate – a simple hypothesis – a complex hypothesis involves more than just two variables. It points out multiple variables and how they interlink with each other. The effects aren’t just limited to cause-and-effect but can be interactive or combined impact-dependent variables too – for instance,’Diet and exercise affect weight loss and heart health.’ Here, diet and exercise are your independent factors influencing multifold aspects like weight loss (a dependent variable) alongside heart health(another dependent variable).

Directional Hypothesis: Definition and Examples

One might argue that the path laid by a directional hypothesis is less twisted as it predicts the directionality of an effect – whether one variable will increase or decrease another variable. An example here could be “Cutting down on alcohol will reduce liver disorders.” Here a reduction in ‘drinking alcohol’ implicitly identifies fewer occurrences of ‘liver disorders.’

Non-directional Hypothesis: Definition and Examples

Sometimes science requires open-ended answers; henceforth comes into play our non-directional hypothesis which merely stipulates that there’s going to be an impact without specifying its course – good, bad or otherwise. For example, “Exposure to secondhand smoke influences lung health.” It infers that there’s an effect on ‘lung health’ due to ‘secondhand smoke,’ without indicating if it’s an improvement or deterioration.

Null Hypothesis: Definition and Examples

The null hypothesis, often symbolized as H0, makes things pretty straight with assumptions; basically, it purports no existence of a relationship between the variables. Researchers utilize this hypothesis chiefly for statistical testing. In lay terms – “Smoking is not linked to lung cancer.” Here a nonexistence of association is suggested between ‘smoking’ and ‘lung cancer.’

Associative and Causal Hypothesis: Explanation and Examples

Now leaving the train station named Null-ville we enter into quite associative terrain where the associative hypothesis foretells ‘relationships’ but are shy when it comes to cause-effects. An instance could be “Students scoring high also tend to play chess.” These fellows here don’t claim that playing chess outrightly shoots up scores yet suggests a specific pattern.

On another spectrum brightful cause-effect claims jump in bravely shouting out not just relationships but boldly stating their causes too – “Consumption of fast food leads to obesity” is being so certain about fast food consumption (cause) escalating obesity levels(effect).

Navigating through these alternative hypotheses and variants allows us to step into researchers’ shoes better while also helps defining complex constructions bit by bit, making them simple outcomes anyone can interpret.

Developing and Testing a Hypothesis

In the world of research, it’s not uncommon to hear someone say “Let’s define hypothesis!” This term may seem complex at first glance, but its essence falls within our natural instinct to question and learn. To give structure to this innate curiosity, we form hypotheses and navigate through the rigorous process of testing them.

Process of Formulating a Hypothesis

Forming an effective hypothesis is both an art and a science. It involves finding a perfect blend between creativity and logical reasoning. Here are some simple yet essential steps you’d want to follow:

Identify Your Research Question – The first step towards formulating a hypothesis is defining your research question based on preliminary observations or literature review.
Conduct Thorough Literature Review – Once your question is in place, an extensive read about what has already been studied can help refine it further.
Create Tentative Explanation – Develop a preliminary answer based on your knowledge and understanding which will serve as your tentative explanation or hypothesis.
Refine Your Hypothesis : Refine this initial guess considering available resources for empirical testing, ethical implications, and potential outcomes.

Remember that the key is formation clarity in statement-making; overly complex language might obscure rather than clarify your central idea.

Importance of Testing a Hypothesis Through Empirical Research Methods

Testing a hypothesis isn’t simply about proving it right or wrong; it’s much more refined than that – it’s about validation and advancement of human knowledge. By applying empirical methods such as observation or experimentation, logic meets practice in real-world scenarios.

These hands-on approaches afford us precious insights into how our theories hold up under scrutiny outside the confines of abstract thought alone.

Validity Confirmation : Empirical testing helps confirm if our predictions were correct or not, providing validation for our presumptions.
Understanding Relationships : Testing allows us to assess the relational dynamics between variables under investigation.
Promotes Scientific Inquiry : Empirical testing encourages a systematic and objective approach to understanding phenomena, which lies at the heart of scientific inquiry.

Consider this: hypotheses are our best-educated guesses – smart hunches rooted in what we know so far. To move beyond guessing and into knowledgeable assertion, we define hypothesis structure as one that can be empirically tested. Only then do we truly start to shape our understanding with any level of certainty.

Examples of Hypotheses in Different Fields

Indeed, it’s fundamental to understand that hypotheses are not confined to a single discipline but span across numerous fields. To better illuminate this, let’s delve into various examples.

Examples of Hypotheses in Scientific Research Studies

In the realm of scientific research studies, hypotheses play a pivotal role in shaping the basis for investigations research hypotheses and experiments. Let’s consider an elementary example: studying plant growth. A researcher might formulate the hypothesis – “If a specific type of fertilizer is used, then plants will grow more rapidly.” This hypothesis aims to validate or refute the assumption that given fertilizer perceptibly affects plant growth rate.

Another common example arises from investigating causal relationships between physical activity and heart health. The scientist may hypothesize that “Regular aerobic exercise decreases the risk of heart disease.”

Examples of Hypotheses in Social Sciences

When we transition towards social sciences, which deals with human behavior and its relation to societal constructs, our formative definitions undergo a change as well.

Imagine researchers examining how socioeconomic status influences educational attainment rates. They could pose a hypothesis saying, “High socioeconomic status positively correlates with higher levels of formal education.” This hypothesis attempts to tie economic background directly to education outcomes.

The correlation between gender diversity within workplace teams and improved business performance presents another illustration. A possible hypothesis could be – “Teams comprising diverse genders exhibit superior business performance than homogenous teams.”

Examples of Hypotheses in Psychology

Within psychology – the study dedicated to how individuals think, feel, and behave; clearly stated hypotheses serve as essential stepping stones for meaningful findings and insights.

Take, for instance, predicting performance under pressure: psychologists may propose an assumption like – “Stress triggers increased errors on complex tasks”. Or when researching cognitive development in children – they may hypothesize – “Language acquisition accelerates once children start attending school”.

Examples of Hypotheses in Medical Research

Lastly but importantly, in medical research, well-articulated hypotheses help probe pressing healthcare questions and identify effective treatments.

For instance: “Patients receiving chemotherapy experience significant weight loss”. Or regarding disease transmission during pandemics – they might propose “Regular hand sanitation reduces the risk of COVID-19 infection.”

In conclusion, these examples hopefully underline the importance and versatility of a hypothesis in scientific inquiry. Irrespective of its utilization within various research fields, a scientific hypothesis still essentially remains an educated assumption that offers direction and purpose to the investigation. Interestingly enough, each study’s defined hypothesis sets forth a path leading towards a better comprehension of our world and life within it.

Common Mistakes to Avoid when Formulating a Hypothesis

Identifying errors that researchers often make when developing a hypothesis.

Many researchers, especially those new in the field, may sometimes falter while crafting their hypotheses. Here are some frequently observed mistakes:

Framing Vague Hypotheses : Clarity is vital when defining your hypothesis. A common pitfall involves creating an ambiguous statement which leaves room for multiple interpretations. This hinders precise data collection and analysis.
Formulating Unfalsifiable Hypotheses : These are statements that cannot be proven false because they don’t connect to observable or measurable variables.
Targeting Unachievable Results : Often, there is an inclination to develop complex hypotheses expecting groundbreaking findings. However, it’s crucial to limit the scope according to practical constraints and possibilities.
Ignoring Null Hypothesis : The null hypothesis provides a means of contradiction to the alternative hypothesis being tested, making it essential for any research study.

Tips for avoiding these mistakes

After identifying the commonly made errors when forming a hypothesis, let’s now consider some proactive measures you can adopt:

Crystallize Your Thoughts : Before you articulate your hypothesis, refine and clarify your ideas first. Define the parameters of your study clearly and ensure your proposition directly aligns with them.
Keep It Simple : Stick with simplicity as much as possible in describing expected relationships or patterns in your research subject area. Remember: A simpler hypothesis often leads to effective testing.
Embrace Falsifiability . To avoid making unfalsifiable claims, learn how to craft ‘If – Then’ statements articulately in your define hypothesis process.
Remember the Null Hypothesis : Always formulate and account for a null hypothesis—a statement that negates the relationship between variables—for robust results validation.

In truth, it takes practice to strike the right balance and formulate a solid, practical hypothesis for your research. With these tips in mind, you’re better equipped to avoid common pitfalls that can compromise the quality of your investigation as they guide your approach when you define hypotheses.

Evaluating and Refining a Hypothesis

Laying out a hypothesis is merely the first stage of an intricate journey. Testing and refining this conjecture is equally pivotal in perfecting your next scientific method of undertaking. This pathway comprises evaluation for validity, and relevance, followed by refinement through research findings.

Methods for Assessing the Validity and Relevance of a Hypothesis

To define a hypothesis of meticulosity, we need to subject it to rigorous scrutiny. Utilizing statistical tests enables you to judge the validity of your hypothesis. Here’s a brief look at some key methods that can assist in assessing your theory:

Empirical Testing : Conduct experiments or surveys as per the requirements of your study.
Consistency Check : The hypothesis should remain consistent with other established theories and laws within its field.
Falsifiability principle : Proposed by Karl Popper, a valid hypothesis must be capable of being proven wrong.

Let me reemphasize here, that relevance plays an integral part too especially when defining hypotheses linked with pragmatics like social sciences or business studies.

A relevant hypothesis will hold significance to not just existing knowledge but also pave the way for future work within the particular area of expertise. It should address gaps in current scientific theories while shedding light on possible solutions.

Ways to Refine and Modify a Hypothesis Based on Research Findings

Our job doesn’t end up on developing an initial proposition; it’s crucial to use findings from our research to refine that preliminary conception further. This essential process breathes life into what was once purely speculative.

While refining your conjecture can sound daunting initially, I assure you it’s nothing more complicated than diagnosing any missing links between your original theory and novel evidence you’ve discovered along this research journey.

If H0 (null hypothesis) contradicts your empirical results, then getting back onto the drafting board becomes necessary for crafting H1 (alternative hypothesis). This scientific cycle of formulating, testing then reformulating the hypotheses can continue till we eventually reach statistically significant results.

Remember, it’s important to be open-minded and responsive towards indications from your research findings. They will guide you intuitively in tweaking your working hypothesis in sync with your target goals.

Hence we must embrace this intricate art of defining a hypothesis while simultaneously embracing its dynamic nature which requires periodic refinement based upon insightful feedback from meticulous research.

Summarizing the Key Points About the Definition and Characteristics of a Hypothesis

Having delved into the concept extensively, we can confidently define a hypothesis as an informed and testable guess or prediction that acts as a guiding light in research studies and scientific investigations. When formulated correctly, it comprises two essential elements: clarity and specificity. It should be free from ambiguity, allowing other researchers to easily understand its proposed idea and the direction the study is heading.

In addition, a robust hypothesis exhibits predictability. As a researcher, you’re not only stating what you think will happen but also defining the variables in your experiment – your assumption confines your investigation’s parameters to make it manageable. Lastly, remember that any meaningful hypothesis must be verifiable — capable of being supported or refuted through data collection and analysis.

Reiterating the Importance of Hypotheses in Scientific Inquiry and Research

This discourse wouldn’t be complete without reaffirming how indispensable hypotheses are within scientific explorations and research inquiries. A conceptualized hypothesis serves as a foundational block upon which every aspect of a research project is built. It directs your observations along assumed patterns, thereby saving time during investigations.

We also need to note that formulating hypotheses promotes critical thinking skills among researchers because they require logical reasoning backed by empirical evidence rather than just empty conjectures.

Henceforth, whether you’re treading through unchartered waters of complex scientific endeavors or conducting social science research with less strict rules for predictions – keeping these insights on “define hypothesis” at hand would surely enhance your journey towards revealing valuable truths.

In essence, cultivating a comprehensive understanding of what constitutes a well-formed hypothesis not only lends credibility to our investigative ventures but also enables us to bring precision, focus, and relevance to our chosen field of exploration. The power lies in its simplistic yet profound ability to guide us from uncertainty towards concrete evidential findings – truly embodying scientific inquiry’s spirit!

Unlock the Power of Visualization with Mind the Graph: Elevate Your Hypothesis to New Heights

As a scientist, your hypothesis is the cornerstone of your research journey. But what if you could take it beyond mere words and equations, and transform it into a visual masterpiece that captivates your audience? Enter Mind the Graph , your ultimate ally in scientific visualization. With our intuitive platform, you can seamlessly translate complex hypotheses into stunning graphs, charts, and illustrations that speak volumes. Whether you are presenting at a conference, publishing a paper, or simply sharing your findings with the world, Mind the Graph empowers you to convey your hypotheses with clarity, precision, and undeniable impact. Join the scientific revolution today and let your hypotheses shine like never before with Mind the Graph.

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Fabricio Pamplona is the founder of Mind the Graph - a tool used by over 400K users in 60 countries. He has a Ph.D. and solid scientific background in Psychopharmacology and experience as a Guest Researcher at the Max Planck Institute of Psychiatry (Germany) and Researcher in D'Or Institute for Research and Education (IDOR, Brazil). Fabricio holds over 2500 citations in Google Scholar. He has 10 years of experience in small innovative businesses, with relevant experience in product design and innovation management. Connect with him on LinkedIn - Fabricio Pamplona .

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Developmental Psychology Topics

Topics for research, papers, and other projects

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Childhood Topics
Adolescence Topics
Adulthood Topics
How to Choose
Tips for Students

Are you looking for a developmental psychology topic for a psychology paper , experiment, or science fair project? Topics you might pick can range from prenatal development to health during the final stages of life.

Developmental psychology is a broad topic that involves studying how people grow and change throughout their whole lifetime. Topics don't just include physical growth but also the emotional, cognitive, and social development that people experience at different stages of their lives.

At a Glance

The following are just a few different topics that might help inspire you. Remember, these are just ideas to help you get started. You might opt to explore one of these areas, or you might think of a related question that interests you as well.

Developmental Psychology Topics on Childhood

Could packaging nutritious foods in visually appealing ways encourage children to make healthier food choices?
Do children who listen to music while studying perform better or worse on exams?
Do students who eat breakfast perform better in school than those who do not eat breakfast?
Does birth order have an impact on procrastination ? Are first-borns less likely to procrastinate? Are last-borns more likely to put off tasks until the last minute?
Does teaching infants sign language help or hinder the language acquisition process?
How do parenting styles impact a child's level of physical activity? Are children raised by parents with permissive or uninvolved parents less active than those raised by parents with authoritative or authoritarian styles?
How does bullying impact student achievement? Are bullied students more likely to have worse grades than their non-bullied peers?
Which type of reinforcement works best for getting students to complete their homework: a tangible reward (such as a piece of candy) or social reinforcement (such as offering praise when homework is completed on time)?

Developmental Psychology Topics on Adolescence

What factors tend to influence the onset of depression in teens and young adults?
How do peer relationships influence identity formation during adolescence and young adulthood?
What impact do parent-child relationships have in predicting substance use among teens and young adults?
How does early substance use during adolescence impact impulsivity and risk-taking during early adulthood?
How does technology use during adolescence influence social and emotional development?
How does social media use influence body image among teens?
What factors contribute to success during the transition from the teen years to early adulthood?
How do cultural differences impact different aspects of adolescent development?

Developmental Psychology Topics on Adulthood

Are older adults who rate high in self-efficacy more likely to have a better memory than those with low self-efficacy?
Do the limits of short-term memory change as we age? How do the limits of short-term memory compare at ages, 15, 25, 45, and 65?
Do mental games such as word searches, Sudoku, and word matching help elderly adults keep their cognitive skills sharp?
How do explanations for the behavior of others change as we age? Are younger adults more likely to blame internal factors for events and older adults more likely to blame external variables?

Choosing Developmental Psychology Topics

Developmental psychology is a huge and diverse subject, so picking a topic isn't always easy. Some tips that can help you choose a good developmental psychology topic include:

Focus on a specific topic : Make sure that your topic isn't too broad to avoid getting overwhelmed by the amount of information available
Have a clear question or hypothesis : Your research question should be focused and clearly defined
Do some background research : Spend some time reviewing the existing literature to get a better idea about what you want to cover with your topic
Consider developmental theories : You might consider analyzing your topic through the lens of a particular theory of developmental psychology
Check out recent research : Use research databases to find the most recently published research on your topic

Before you start working on any paper, experiment, or science project, the first thing you need to do is understand the rules your instructor has established for the assignment.

Also, be sure to check the official guidelines given by your teacher. If you are not sure about these guidelines, ask your instructor if there are any specific requirements before you get started on your research .

If you are going to actually conduct an experiment , you need to present your idea to your instructor to gain their permission before going forward. In some cases, you might have to also present your plan to your school's Institutional Review Board.

Tips for Researching Developmental Psychology Topics

After you have gotten to move forward with your chosen topic, the next step is to do some background research. This step is essential! If you are writing a paper, the information you find will make up your literature review.

If you are performing an experiment, it will provide background information for the introduction of your lab report . For a psychology science project, this research will help you in your presentation and can help you decide how to best approach your own experiment.

What This Means For You

Choosing a topic for a developmental psychology experiment, paper, or project can be tough! The ideas above can be a great place to start, but you might also consider questions you've had about your own life. Once you have a general idea for your topic, narrow it down, do some background research and talk to your instructor.

Nielsen M, Haun D. Why developmental psychology is incomplete without comparative and cross-cultural perspectives . Philos Trans R Soc Lond B Biol Sci . 2016;371(1686):20150071. doi:10.1098/rstb.2015.0071

Leite DFB, Padilha MAS, Cecatti JG. Approaching literature review for academic purposes: The Literature Review Checklist . Clinics (Sao Paulo) . 2019;74:e1403. Published 2019 Nov 25. doi:10.6061/clinics/2019/e1403

Grady C. Institutional review boards: Purpose and challenges . Chest . 2015;148(5):1148-1155. doi:10.1378/chest.15-0706

Kim WO. Institutional review board (IRB) and ethical issues in clinical research . Korean Journal of Anesthesiology . 2012;62(1):3-12. doi:10.4097/kjae.2012.62.1.3

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Article Contents

Introduction, data analysis, acknowledgments, author contributions, conflicts of interest.

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Superhero Pretense, Superhero Identification, and Risk-Taking in Preschool-Aged Children

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Casie H Morgan, David C Schwebel, Superhero Pretense, Superhero Identification, and Risk-Taking in Preschool-Aged Children, Journal of Pediatric Psychology , Volume 49, Issue 4, April 2024, Pages 234–243, https://doi.org/10.1093/jpepsy/jsad045

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The preschool years represent a stage of rapid human development, hallmarked by exploring the environment through gross and fine motor movement and imaginative pretend play. This exploration is developmentally appropriate but also presents risks for injury, the leading cause of death for preschool-aged children. Common injuries reflect exploration and risk-taking exhibited during play, and play may be particularly risky when children imitate risky models like superheroes. Frequent exposure and subsequent identification with superheroes are concerning because the media glorifies superheroes, creating social learning effects on children and promoting play situations where children may attempt superhuman abilities and hurt themselves. This study examined the relations between pretend play, superhero identification, and children’s risk-taking.

One hundred five children aged 4–5 years old were randomly assigned to either a superhero- or school- themed, story-based protocol. In both conditions, children engaged in three identical behavioral tasks to assess risk-taking. Identification with superheroes was measured using parent-report questionnaires and child interviews.

Pretending to be a superhero was not associated with increased risk-taking behavior acutely, but identification with superheroes was associated in some analyses with preschool children’s broader risk-taking behavior. Across risk-taking behavior tasks, children with high superhero identification pretending to be superheroes tended to take the most risks.

Given the popularity of superhero media and the present results suggesting superhero identification may relate to injury-risk situations during play, prevention efforts should consider ways to reduce young children’s exposure to superheroes and/or mitigate injury risk during active pretend play.

Play allows children to grow, providing experiences of arousal, exhilaration, happiness, and carefreeness ( Sutton-Smith, 1997 ). Play settings also represent a common location for risk-taking. We focus presently on the intersection of two aspects of play: risky play and pretend play. Risky play comprises stimulating and exciting play involving the risk of physical injury ( Sandseter, 2009 ). Pretend play combines pretense with play . Although not innately risky, it can become so when children imitate characters with risk-taking tendencies. For example, a child pretending to be Superman may imitate superhuman flying ability and jump off a bunkbed, incurring a broken limb. Risky play behaviors are one mechanism contributing to the roughly 1.7 million Americans aged 1–5 who suffer from a serious, nonfatal injury annually and the tragic deaths of about 1,400 children ( NCIPC, 2020 ).

The present study considers theoretical and behavioral underpinnings behind why children may imitate risky superhero behaviors during pretend play. Identification theory and social learning theory offer two conceptualizations. Identification theory comprises the process through which individuals identify with social agents in their immediate and personal environments, including celebrities and fictional media characters. Superhero characters represent highly identifiable role models for contemporary children due to their age-targeted popularity and ubiquity (e.g., PJ Masks, DC Super Hero Girls ), relatable alter-egos (Peter Parker as Spiderman), and charismatic personalities.

Social learning theory ( Bandura, 1971 ) suggests children mimic behavior of those they respect and identify with, including both aggressive ( Coyne et al., 2017 ) and risk-taking ( Anderson & Bushman, 2002 ; Fischer et al., 2007 ) behaviors they view in media. Superheroes frequently engage in physical risks and display superhuman skillsets that real-world children cannot possess. Superheroes are also often portrayed as risky decision-makers whose behavior is romanticized, typically with minimal negative impact. Observing risky behaviors followed by positive outcomes may lead children to risk-taking.

Despite the theoretical basis for associations between media exposure and risky pretend play, empirical support concerning the impact of identification with and modeling of superheroes on risky behavior during pretend play is limited. One study examined influences of both immediate media exposure from watching a superhero television show and parent-reported long-term superhero media exposure on children’s risk-taking outside of pretense. It found that lifetime superhero exposure was related to children’s risk-taking in both behavioral and self-report assessments, but immediate superhero exposure was not ( Morgan et al., 2021b ). A second study used parent-and child-report measures to assess relations between media exposure and child behavior. It found children imitate both aggressive and prosocial behaviors they view in superhero media ( Coyne et al., 2017 ).

The present study extends previous findings to address how superhero media risk behaviors may promote risk-taking while children are actively pretending to be superheroes. Despite evidence of links between superhero media and children’s risk-taking in a few previous studies, no research has examined pretend risk-taking behavior with this age group while they are actively pretending to be superheroes. Two broad research aims were addressed: (1) Determine if children take more risks while actively pretending to be superheroes compared to while not actively pretending to be superheroes, and (2) examine whether children’s level of identification with superheroes moderates the impact of superhero pretend play on risk taking.

Within those two broad aims, we examined three specific hypotheses. First, we expected children randomly assigned to pretend to be a superhero would take more risks while pretending to be superheroes than children in a control condition pretending to be in school. Second, we expected identification with superheroes would increase risky behavior while pretending to be a superhero. Third, we expected that superhero identification would moderate the relation between pretend play and risk-taking such that risk-taking would be greater among children pretending to be superheroes than children pretending to be in school because children’s risk-taking would be heightened through priming of superhero traits.

Participants

Children aged 4 or 5 years and a parent participated in a 90-minute laboratory visit. Families were recruited through a locally representative database of families interested in research participation as well as word-of-mouth, personal contact, social media, and community advertising. All participants were fluent in English, and exclusion criteria were minimal. During study enrollment screening, parents responded to a single question: Has your child ever seen a superhero show or movie? If parents responded “No,” then their child would have been excluded; no children were excluded based on this criterion. Participants were also excluded for cognitive, developmental, or physical disabilities (e.g., use of a wheelchair, autism spectrum disorder, blindness) that prohibited following simple verbal instructions, providing verbal responses, or engaging in physical activity. Two participants were excluded based on these criteria. One additional participant was excluded due to behavior concerns that interfered with valid adherence to the study protocol.

Participants included 105 children with an average age of 5.01 years ( SD = 0.57) and their parents. Children were 54.7% male, 63.2% White, and 94.3% non-Hispanic/Latino. Families were mostly middle- to upper-income level (53.5% > $79,000/year) and parents mostly college-educated (73.6% of primary caregivers had at least bachelor’s degree). Table I details participant characteristics.

Descriptive Statistics for Participant Characteristics

Previous childcare/education included: daycare, pre-k, preschool, early head start, head start, kindergarten, first grade.

N = 7 missing: n = 4 missing for school condition, n = 3 missing for superhero condition.

Materials/Measures

Data were collected from both primary caregivers and children. Predictor variables and experimental conditions are detailed in the following sections, followed by the three activities assessing the primary child risk-taking outcome.

Child/Family Demographics

Child sex, race, ethnicity, age, caregiver education, family income, and child daycare/preschool history were assessed through parent report.

During the laboratory visit, children engaged in a story-based protocol with three behavioral tasks to assess risk-taking incorporated into the plotline of either a pretend superhero-based or school-based story, randomly assigned across participants. Children were randomly assigned to one of two pretend conditions, superhero or school. In the superhero condition, children pretended to be the superhero protagonist in an adventurous story. Similar to previous studies (e.g., Coyne et al., 2022 ; White & Carlson, 2016 ), beginning in the lab’s waiting room they selected and dressed in a superhero costume (e.g., Spiderman, Super Girl). Costume selection was standardized so all children had identical choices and all costumes included a cape, mask, and wristband. The story plot winded throughout decorated lab space and children engaged in the risk-taking tasks. Each task incorporated aspects of the storyline relevant to risk-taking and their superhero “responsibilities.” For example, the first task assessed children’s perceived physical ability ( Ability Test , detailed below). The research assistant directed children, calling them by their chosen pretend superhero, with instructions like, Okay Batman! It’s time to test your new powers before we check on the citizens of the Safety Lab! Follow me—we’ll observe your skills in our Super-Secret Headquarters. Children wore costumes throughout the study and researchers made frequent references to reinforce the superhero storyline and pretending throughout the protocol.

Children in the school condition walked through the experimental protocol in a similar pretend fashion, but their story was set in school. The school protocol was engaging like the superhero condition, and sex neutral, but had no references to superheroes or superhero activities. The laboratory was decorated to look like a preschool or kindergarten classroom. As an example, the Ability Test parallels physical fitness tests children might complete at school, so researchers said, Okay (Child’s name)! We are going to walk down the hall for PE ! It’s your first day at Safety Lab School, so we need to learn what physical activities you can do. Follow me. Children in the school condition completed the same tasks in the same order as children in the superhero condition. They wore backpacks rather than superhero costumes and selected a colored notebook and pencil with decorative eraser to place in their backpack.

Fidelity checks were conducted during and after the experiment to ensure children engaged in the pretense conditions. Both child self-report and researcher assessment indicated strong engagement in the pretense.

Superhero Identification

A superhero identification composite was calculated by aggregating assessments of the following three interrelated constructs, all adapted from previous research ( Coyne et al., 2017 ; Morgan et al., 2021b ): knowledge of superhero characters, affiliation with superhero characters, and imitation of superhero behaviors. Knowledge was assessed using 22 pictorial prompts of popular superhero characters. The more characters children recognized, the higher their score. Affiliation was measured using two parent–report questions asking about their children’s favorite and second-favorite superhero: How much does your child identify with their favorite (second favorite) superhero, on a scale of 1–7? In other words, how much do they want to be like their favorite superhero, in terms of appearances, personality, characteristics, etc.? Higher scores reflected higher affiliation. Imitation was captured using nine parent–report questions assessing children’s frequency of imitating specific superhuman powers (e.g., How often does your child pretend by wearing a cape like Superman or Batman? ).

All three outcome scores were standardized, then averaged into the constructs of knowledge, affiliation, and imitation, and then combined into a single composite. Higher scores indicate higher superhero identification. Concordance across the three constructs was strong (average intercorrelation r = .42; α = .89).

Risk-Taking Tasks

Three measures of risk taking were adopted from established assessments of children’s risk-taking intentions and behaviors in play situations. Each offered ecologically valid assessment of real-world scenarios without putting children at risk of actual injury.

Ability test : Ability Test compared children’s perceived ability to perform a physical activity to their actual ability ( Plumert, 1995 ). Three activities, vertical reach task, stepping task , and crouching task were conducted. The vertical reach task requires a child to remove a toy from an adjustable shelf while standing on tip toes. The stepping task demands stepping across two parallel sticks on the floor without jumping. The crouching task involves the child reaching out from a squat position for a toy duck on a wooden block without touching hands or knees on the floor.

All three tasks were administered through four steps. First, baseline measures, which were collected prior to randomization into the pretend condition, determined each child’s maximum ability levels. Second, with children outside the experimental room, researchers arranged the activities to appropriate positions based on baseline measurements. Each task was scaled to match children’s individual ability and was adjusted, always with children absent, four times. Each adjustment represented distinct levels of difficulty: (1) well-within (13% below children’s previously measured maximum ability); (2) just-within (at maximum ability); (3) just-beyond (8% above maximum ability); and (4) well-beyond (13% above maximum ability). Children therefore engaged in 12 trials total, grouped into four blocks of three (four vertical reach trials, four stepping trials, and four crouching trials). Task order and difficulty were both randomly ordered.

Third, for each trial, children were positioned in the “starting position.” In all scenarios, if children judged they could perform the task, they proceeded to try it. If they did not think they could complete the task, it was postponed until the fourth step of the experiment. Fourth, at the end of the 12 trials, the tasks children deemed too difficult to perform were reset and attempted. This provided a validity check to ensure tasks were calibrated correctly. If at any point, it was observed that a task was calibrated incorrectly, that trial was dropped from analysis.

All activities were recorded through a one-way mirror and subsequently video-coded to calculate the percentage of correct judgments at each ability level. The primary outcome of interest for the present study was children’s overestimation of ability, conceptualized as children judging they could complete a task that was actually just or well beyond their ability.

Cohen’s κ was computed to determine agreement between two researchers on coding of children’s responses during the task. Reliability across tasks ranged from κ = .92 to κ = 1.00, demonstrating strong agreement. An average just beyond performance score was calculated by averaging children’s responses for the reach, step, and crouch at the just beyond level, and an average well beyond performance calculated similarly for tasks at the well beyond level. These two outcomes comprised two of the study’s four risk outcomes.

Activity room : The Activity Room assessed children’s risky play behaviors in an ecologically valid setting—a playroom with the following items available: Hopper Ball (45-cm diameter bouncy ball with handle); plastic slide (99-cm high, with 97-cm long slide length); 1.83 meter-long balance beam (5.08-cm high); ball pit (summer wading pool, 1.14-m diameter, 20.1-cm high, filled with colorful plastic balls); soft football, basketball, and soccer ball; hula-hoop; and ball on an elastic string attached to a wrist strap ( Morgan et al., 2021a ). It also included an armchair, a rug with a road mapped on it, a rug with the alphabet, and a bucket of books that would not typically promote risk-taking. The floor was padded.

At the start of the task, children were told, You’ve been working so hard, it’s time for a break in the free play area! Similar to other tasks, the story protocol primed the child’s pretend condition. Children in the superhero condition received an additional prompt: This room is all about having fun and doing what a superhero does! Just play, have fun, and be a superhero. Children in the school condition received the additional prompt: This room is where we take a break from schoolwork and learning! You can play with any toys you want in the play area. Children played alone in the activity room and were continuously monitored through a one-way mirror for 5 min, with all activity was videotaped for subsequent coding. The primary outcome measure, intentional risk-taking , was coded when children engaged in thrilling and exciting gross motor activity that involved at least some risk of physical injury to self. Examples include jumping off the slide and running across the balance beam.

Coding of activity room outcomes was conducted in four steps. First, a comprehensive coding guide was adapted from previous research ( Morgan et al., 2021a ; Morrongiello et al., 2010 ; Morrongiello & Dawber, 1998 ; Schwebel et al., 2006 ) and a time-sampling approach applied by dividing the 5-min session into 10 30-s time samples. Presence or absence of each target behavior was coded in a binary manner during each time sample, and the percentage of segments in which the target behaviors occurred was calculated for analysis.

The second coding step involved multiple researchers jointly viewing tapes to refine coding definitions iteratively and finalize the coding scheme. Third, interrater reliability was established by two independent raters. Percent agreement was calculated among a randomly selected 15% of observations and strong reliability was achieved (average interrater agreement = 96%; overall kappa = 0.94). Last, the two raters split coding of the remaining videos.

Picture task : Adapted from previous research ( Morgan et al., 2021b ), in the picture task children viewed 10 illustrations of risk behavior and settings, one at a time. Examples include a child standing on the edge of a bathtub and two children jumping on a bed. As children viewed each situation, researchers offered a brief explanation, such as, You are getting ready to take a bath but then remember your bath toy is on the shelf above the bathtub . Each scene ended with a prompt beginning with Would you… and then a description of the behavior (e.g., Would you stand on the edge of the bathtub so that you can reach the toy? ). Children were prompted to answer “Yes” or “No,” and decisions were coded dichotomously as safe or unsafe. Scores across the 10 scenarios were summed to produce a single risky behavior score, with higher scores indicating greater risk-taking intentions.

The study protocol was approved by the Institutional Review Board at University of Alabama at Birmingham. During the 90-min visit, parents and children first completed informed consent and verbal assent procedures, followed by baseline Ability Test measurements and assessment of children’s superhero identification. Children were then randomly assigned to condition and engaged in the behavioral tasks in the following order: ability test, picture sort, activity room. Parents completed surveys in a separate room. After both children and parents were finished, families were reimbursed for their time and children selected a toy prize. Anonymized data reported in this article will be provided to qualified users upon reasonable request.

Descriptive statistics were computed first. Differences in demographic and other baseline variables were compared across the two randomly assigned groups using independent samples t -tests for continuous variables and chi-square for categorical data. Following descriptive analyses, t -tests and chi-square analyses assessed differences between randomized groups and relations between child age and primary outcomes and child gender and primary outcomes. No noteworthy data patterns arose. To test whether children took more risks while pretending to be superheroes versus in school, a one-way MANOVA assessed ability test scores jointly and independent sample t -tests examined activity room and picture sort scores. To evaluate whether broad identification with superheroes associated with children’s risky behavior, including specifically when children pretended to be superheroes, moderation analyses were conducted using a hierarchical linear regression model in the SPSS PROCESS macro ( Hayes, 2013 ). Moderation analyses were specified prior to hypothesis testing and simple slope analyses were conducted if the interaction between the predictor variable (condition) and moderator (superhero identification) was significant. Sex was included as a covariate in the well beyond ability test moderation analysis due to significant differences in risk-taking emerging between boys and girls only for that outcome. During assumption testing, we discovered the ability test and picture sort outcomes had somewhat nonnormal distributions. Transformations and truncation did not substantially improve normality, so analyses proceeded as planned given the robustness of moderation analyses to nonnormal distributions ( Ernst & Albers, 2017 ). All other statistical assumptions were met.

Preliminary Analyses

Table I lists demographic characteristics of the sample. No differences emerged between randomly assigned conditions in child sex, child race, child ethnicity, family income, or child age. Descriptive data were computed for the four risk outcomes: just beyond performance (overall M = 0.09, SD = 0.19), well beyond performance (M = 0.17, SD = 0.25), activity room (M = 38.48, SD = 24.29), and picture task (M = 3.14, SD = 2.77). Bivariate correlations between the risk outcomes for the overall sample yielded a significant relation only between the two ability test tasks ( r = .39, p < .001). Bivariate correlations between the risk outcomes within the subsamples of only girls ( r = .36, p < .05) and only boys ( r = .50 p < .001) also demonstrated a significant relation only between the two ability test tasks. Analyses to evaluate bivariate relations between superhero identification, age, and risk outcomes yielded no significant relations. Comparisons across boys and girls in risk taking revealed a significant difference for well beyond performance t (103) = −2.83, p = .006, with males taking more risks than females, but no sex differences were detected for just beyond performance, activity room, or picture task. Given these findings, primary analyses were conducted with sex included only in the well beyond model and child age omitted from the models.

Hypothesis 1: Pretense Only

To evaluate group differences between children randomly assigned to pretend to be superheroes versus at school, a one-way MANOVA was computed to determine the effect of pretend condition on risk-taking in the just beyond and well beyond ability tasks. No statistically significant differences emerged between conditions on the combined dependent variables, F (1, 102) = 0.56, p = .58. An independent sample t- test evaluated the effect of pretend condition on risky activity room play. No statistically significant difference emerged, t (1, 103) = 1.31, p = .19. Finally, an independent sample t -test examined the effect of condition on risk-taking in the picture sort task, and no statistically significant difference emerged, t (98) = 1.28, p = .20 (see Table II ).

Results Comparing Risk Taking Across the School and Superhero Pretend Conditions—One-Way MANOVA and Independent t-Tests

Note. M = mean; SD = standard deviation; CI = confidence interval.

Hypotheses 2 and 3: Just Beyond Ability Test

We considered whether broad identification with superheroes was associated with children’s risky behavior, including specifically when children pretend to be superheroes. Four moderation regression analyses were conducted with condition included as a predictor, superhero identification as a moderator, and risk outcomes as dependent variables. The overall model for just beyond performance was not statistically significant, R 2 = .07, F (3, 101) = 2.61, p = .06, and neither condition t (101) = 0.46, β = 0.04, p = .64 nor superhero identification t (101) = −1.11, β = 0.03, p = .27 was related to just beyond performance (see Table III ). However, superhero identification significantly moderated the effect of condition on just beyond performance, [ t (101) = −2.54, β = 0.06, p = .01; Δ R 2 = .06, F (1, 101) = 6.46] and accounted for 6.4% added variation in performance.

Results of Moderation Analyses for Risk Outcomes and Superhero Identification

Note. SE = standard error; SH ID = superhero identification.

Condition interpretation: 0 = school, 1 = superhero.

Sex interpretation: 0 = female, 1 = male.

p < .05,

p < .01.

Simple slope analyses showed that condition was significantly related to just beyond performance only at lower levels of superhero identification, one SD below the mean ( β = 0.53, p = .04), suggesting that among children with lower levels of superhero identification, children pretending to be in school took significantly more risks than children pretending to be superheroes. No significant differences emerged at moderate ( β = 0.04, p = .65) or higher levels of superhero identification ( β = 0.05, p = .14) (see Figure 1 ). Aligning with our hypothesis, descriptive data suggest children with high superhero identification who were randomly assigned to the superhero condition took the most risks among the six subgroups studied (three superhero identification groups by two randomized conditions).

Interaction between condition and superhero identification for just beyond ability test scores. Note. Ability test scores are inverted (100 − original value) so that higher scores indicate greater risk-taking.

Hypotheses 2 and 3: Well Beyond Ability Test

A similar model was computed to predict performance in the ability test well beyond level, but with child sex added into the model given results from preliminary analyses. The overall model was statistically significant, R 2 = .17, F (4, 100) = 5.26, p = .001, but neither condition t (4, 100) = −0.61, β = −0.03, p = .54, nor superhero identification t (4, 100) = −0.70, β = −0.03, p = .49 were significantly related to well beyond performance. The variables accounted for 7.0% added variation in performance. Child sex was significantly related to well beyond performance t (4, 100) = −2.65, β = −0.12, p < .01 (see Table III ). Further, as hypothesized, superhero identification significantly moderated the effect of condition on well beyond ability test performance, t (4, 100) = −3.30, β = −0.26, p = .001; Δ R 2 = .09, F (1, 100) = 10.92.

Simple slope analyses demonstrated that condition was related to well beyond performance only at higher levels of superhero identification, one SD above the mean ( β = −0.18, p = .01), suggesting children pretending to be superheroes took more risks than children pretending to be at school at higher levels of superhero identification, but not at lower ( β = 0.13, p = .06) or moderate levels ( β = −0.03, p = .54) (see Figure 2 ). Again, descriptive data suggest children with high superhero identification and randomly assigned to the superhero condition took more risks than the other subgroups of children.

Interaction between condition and superhero identification for well beyond ability test scores. Note. Ability test scores are inversed (100 − original value) so that higher scores indicate greater risk-taking.

Hypotheses 2 and 3: Activity Room

Next, we constructed a model predicting risky activity room play. The overall model was not statistically significant, R 2 = .07, F (3, 101) = 2.46, p = .067. Neither condition t (4, 94) = 1.24, β = 5.79, p = .22 nor superhero identification t (4, 94) = 0.91, β = 3.57, p = .37 were significantly related to risky play (see Table III ), but as hypothesized, superhero identification significantly moderated the effect of randomized condition on risky play, t (4, 94) = −2.18, β = −17.13, p = .03; Δ R 2 = .04, F (1, 101) = 4.75. The interaction effect accounted for 4.3% added variation.

Simple slope analyses showed that condition was related to risky play only at lower levels of superhero identification, one SD below the mean ( β = 16.00, p = .02), suggesting children pretending to be superheroes took more risks than children pretending to be in school at lower levels of superhero identification, but not at moderate ( β = 5.79, p = .22) or higher levels ( β = −4.42, p = .51) (see Figure 3 ).

Interaction between condition and superhero identification for activity room.

Hypotheses 2 and 3: Picture Sort

Finally, we computed a model predicting picture sort responses. The overall model was not statistically significant, R 2 = .03, F (3, 96) = 1.09, p = .36 and neither condition t (3, 96) = 1.27, β = 0.71, p = .21 nor superhero identification t (3, 96) = 0.14, β = 0.07, p = .89 were related to risk-taking (see Table III ). Additionally, superhero identification did not moderate the effect of condition on risk-taking t (3, 96) = 1.27, β = 1.20, p = .21; Δ R 2 = 0.02, F (1, 96) = 1.62.

Our analysis of relations between superheroes and risk-taking in 4- and 5-year-old children suggests children’s risk-taking behaviors may be slightly influenced by a combination of close identification with superheroes and active superhero pretense. Our first broad aim was to determine if children take more risks while actively pretending to be superheroes compared to while pretending to be in school. We obtained null results, suggesting a broad cross-section of children may not take more risks when pretending to be superheroes versus pretending to be in school. The study’s second broad aim was to evaluate whether children’s level of identification with superheroes moderates the impact of superhero pretend play on risk taking. We found that superhero identification did not independently predict risk-taking, but superhero identification interacted with pretending to be a superhero to predict risk-taking behavior for some outcomes. These interactions presented differently across the risk-taking outcomes we administered.

Children with higher levels of superhero identification who were pretending to be superheroes took significantly more risks than children pretending to be in school in the well beyond ability test. This finding supports our hypotheses and suggests the combination of close identification with superheroes and active pretending to be a superhero may lead children to take more risks in situations where they estimate their physical ability to complete a task. It raises concern from an injury prevention perspective since children’s interpretation of risk is associated with their willingness to attempt potentially injurious physical risks ( Plumert, 1995 ; Sandseter, 2007 ).

Results for the just beyond ability test showed a similar visual pattern ( Figures 1 and 2 ), but statistical significance emerged among children with low levels of superhero identification, where those children pretending to be in school took more risks than children pretending to be superheroes. This finding may reflect an unexpected influence of the school condition on children’s risk-taking. Given the increased ambiguity of judging personal ability in the just beyond test compared to the well beyond test, it is possible that all children were less certain about their ability to complete the task but those pretending to be in school were more motivated to attempt the task because they felt pressure to follow directions and appease the authority-laden research assistant (teacher). Future research should consider the logistics of the ability test instructions to ensure participants understand that there is no right or wrong answer. Future research could also incorporate alternative control groups that do not involve pretending to be in school.

Results from the moderation analysis in the activity room task found that children with low levels of superhero identification pretending to be superheroes took significantly more risks than children with low levels of superhero identification pretending to be in school. As shown in Figure 3 , the simple slopes analysis revealed that risky play for children pretending to be superheroes was at about the same level, regardless of superhero identification. In contrast, there were descriptive differences in risky activity room play among children pretending to be in school across the three levels of superhero identification. Children with lower levels of superhero identification and pretending to be in school had no influence from immediate superhero exposure based on the randomization and demonstrated the lowest percentage of activity room risk-taking among the subsamples studied. Children with high superhero identification in both conditions, plus those pretending to be superheroes, all showed more risk-taking in the activity room. Future research is recommended, but the finding may support results from the well beyond and just beyond ability estimation tasks and reflect a combined moderation influence of superhero identification and pretending to be a superhero on children’s risky play behavior.

Null Results

Our findings concerning the impact of pretense on children’s risk-taking across the full sample were null; children pretending to be superheroes did not take more risks than children pretending to be in school. The null results may be valid and accurate, but several methodological factors may have impacted the results and should be addressed in replication attempts. First, in developing the superhero pretense condition, we expected to encourage imitation and adoption of a specific identity by creating an environment that encouraged pretend play in the child’s randomized role. The children may not have fully embodied the pretend superhero role. Many factors impact active engagement in pretense ( Fein, 1975 ), including collaborative social dialogue and role-taking, symbolic use of objects and actions, knowledge of a script, and ability to improvise ( Bergen, 2002 ). We implemented most of these factors in the research protocol, but the experimental manipulation restricted our ability to enact some key components. Future research might consider observational research designs in naturalistic environments like playgrounds to evaluate if pretend play in these settings yields different results. Alternatively, a longitudinal approach that allows children more time to engage in the pretend role and identify more closely with pretend characters could capture different behavior patterns.

A second explanation for our null results is that the pretend situation we introduced did not always map directly to behavior in the risk-taking tasks. Prompts related to pretend roles generally occurred outside the risk-taking tasks themselves to ensure standardization across conditions. Therefore, when participants faced a risk-taking task, they may have behaved as themselves, outside their pretend role, and then reverted to the pretend role after completing the task. Future research could overcome this limitation through methodological manipulations such as within-subjects designs that evaluate behavior under different pretend roles.

A third possible explanation for our null results is that pretending to be a student in school unexpectedly impacted risk-taking. Interaction with authority looks different for students compared to superheroes. Ninety percent of children in the school condition had previous experience in school settings, so if children were highly engaged in their pretend student roles, they may have internalized anticipated rules and expectations of school settings. As an example, “saying yes” to attempt a task in deference to authority figures like teachers may have translated to artificially higher risk-taking in the ability test protocol among children in the school condition.

Implications

Implications of our findings to parents may actually be reassuring and comforting. Interpreting null findings must always be done cautiously, but our findings seem to indicate that exposure of young children to superhero media is not producing dramatically concerning elevations in risk-taking behavior. Nonetheless, our results indicate the possibility of some minor impact of superhero identification and superhero pretense on children’s risk-taking. From an injury prevention perspective, parental efforts to help children accurately perceive risks, and accurately perceive the extent of their motor ability skills to negotiate those risks, might help reduce injury rates. More intense adult supervision of children pretending to be superheroes is also a logical strategy, as adults can help children learn to judge their physical abilities and intervene when children are preparing to engage in a risky activity. The study results also have implications beyond parenting. The media industry could adjust presentation of risk-taking superhero behavior in media targeting young children, for instance.

Limitations and Conclusions

Our results should be interpreted in the context of study limitations. First, our sample was largely middle- to upper-class and generalizability to children from lower socioeconomic backgrounds is unknown. A second limitation was use of the ability test as a primary measure of risk-taking. That measure had been used previously with children as young as age 7 ( Plumert, 1995 ) but may not have translated well to a younger age group. A third limitation relates to statistical power. Our sample size was designed with 80% power to detect medium effect sizes, but our effect sizes tended to be small rather than medium. A final limitation refers to developmental considerations of the sample. Although our exclusion criteria screened for developmental disabilities, families were not explicitly asked to report medical or psychiatric diagnoses. Given the age range, it is possible that some participants had developmental diagnoses like autism spectrum disorder that impacted children’s ability to engage in pretend play in the way typically-developing children might engage in pretend play.

In conclusion, we found that active pretending by young children to be a superhero was not associated with increased risk-taking, but children scoring high in superhero identification who were actively pretending to be superheroes took more risks on some behavioral tasks. Our findings align both with identification theory and social learning theory. Theory-driven prevention could focus first on decreasing children’s exposure to risky superhero behaviors in media so they identify less with risk-taking characters (reduced impact of social learning). Additionally, theory-driven prevention could center on changing how superheroes are portrayed in media designed for young children so social modeling of character behavior involves less risk (reduced impact of identification theory). Superhero media is likely to remain popular for many years. If superhero identification and pretending to be a superhero play a small role in children’s risk-taking, which our study results suggest, then continued research to clarify risk and implement prevention is warranted.

The authors thank our participants, staff, and school collaborators for their support and efforts on behalf of this project. Communication regarding this article can be directed to [email protected] .

Funding for this research was provided by the American Psychological Association Division 53 Routh Dissertation Grant and American Psychological Association Psychological Science Grant, with additional support from the University of Alabama at Birmingham, Department of Psychology and College of Arts and Sciences. The views expressed are solely those of the authors and do not reflect the official positions of the funding agencies.

Casie Morgan (Conceptualization [lead], Data curation [lead], Formal analysis [lead], Funding acquisition [equal], Investigation [lead], Methodology [lead], Project administration [lead], Resources [equal], Software [lead], Writing—original draft [lead], Writing—review & editing [lead]), David Schwebel (Conceptualization [supporting], Data curation [supporting], Formal analysis [supporting], Funding acquisition [supporting], Investigation [supporting], Methodology [supporting], Project administration [supporting], Resources [equal], Software [supporting], Supervision [lead], Writing—original draft [supporting], Writing—review & editing [supporting]).

None declared.

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Research Hypothesis In Psychology: Types, & Examples
Examples. A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
2.4 Developing a Hypothesis
A hypothesis, on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. ... As Figure 2.2 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook ...
Developmental Psychology Research Methods
Experimental Research Methods. There are many different developmental psychology research methods, including cross-sectional, longitudinal, correlational, and experimental. Each has its own specific advantages and disadvantages. The one that a scientist chooses depends largely on the aim of the study and the nature of the phenomenon being studied.
How to Write a Great Hypothesis
What is a hypothesis and how can you write a great one for your research? A hypothesis is a tentative statement about the relationship between two or more variables that can be tested empirically. Find out how to formulate a clear, specific, and testable hypothesis with examples and tips from Verywell Mind, a trusted source of psychology and mental health information.
Developing a Hypothesis
The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more ...
Looking in on the Children: Using Developmental Psychology as a Tool
The aim of this article is to illustrate how developmental psychology may be used as a tool for hypothesis testing and model building in social psychology. To this end, 5 conceptual themes and I methodological theme linking developmental psychology to social psychology are outlined.
How to Write a Strong Hypothesis
5. Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
Lifespan Development: A Psychological Perspective
Developmental Psychology, also known as Human Development or Lifespan Development, is the scientific study of ways in which people change, as well as stay the same, from conception to death. You will no doubt discover in the course of studying that the field examines change across a broad range of topics. These include physical and other psychophysiological processes, cognition, language, and ...
Developing a Hypothesis
Theories and Hypotheses. Before describing how to develop a hypothesis, it is important to distinguish between a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes ...
Beyond the Core-Deficit Hypothesis in Developmental Disorders
Over and above specific problems with any single theory, this general class of theory is problematic because of the reliance on the very notion of a "core deficit"—something that has been repeatedly debunked both within specific (Happé, Ronald, & Plomin, 2006) and across multiple diagnostic categories (e.g., Pennington, 2006).But in practice, developmental psychologists and ...
Developmental phenomenology: examples from social cognition
A variety of findings in contemporary developmental psychology suggests that pairing is a viable hypothesis for how infants come to perceive other minds. Footnote 30 In the domain where empirical research is most advanced, i.e. action perception, there is even an eminent developmental-psychological theory that is essentially equivalent to the ...
Beyond the core-deficit hypothesis in developmental disorders
Developmental disorders and childhood learning difficulties encompass complex constellations of relative strengths and weaknesses across multiple aspects of learning, cognition, and behavior. Historically, debate in developmental psychology has been focused largely on the existence and nature of core deficits—the shared mechanistic origin from which all observed profiles within a diagnostic ...
Psychological Theories: Definition, Types, and Examples
Behavioral psychology, also known as behaviorism, is a theory of learning based on the idea that all behaviors are acquired through conditioning. Advocated by famous psychologists such as John B. Watson and B.F. Skinner, behavioral theories dominated psychology during the early half of the twentieth century.
Concepts and Categories: A Cognitive Neuropsychological Perspective
Research in developmental psychology has also highlighted other domains of knowledge beyond those motivated by neuropsychological research on patients with category ... The domain-specific hypothesis: a developmental and comparative perspective on category-specific deficits. In: Forde EME, Humphreys GW, editors. Category-Specificity in the ...
Developmental Psychology 101: Theories, Stages, & Research
The American Psychological Association (2020) defines developmental psychology as the study of physical, mental, and behavioral changes, from conception through old age. Developmental psychology investigates biological, genetic, neurological, psychosocial, cultural, and environmental factors of human growth (Burman, 2017).
PDF Developmental Psychology
Developmental Psychology Genetics of Nurture: A Test of the Hypothesis That Parents' Genetics Predict Their Observed Caregiving Jasmin Wertz, Jay Belsky, Terrie E. Moffitt, Daniel W. Belsky, HonaLee Harrington, Reut Avinun, ... hypothesis that parents' polygenic scores for educational attain-ment are associated with warm, sensitive, and ...
Developmental Psychology
Psychological Development of Individuals. The main focus of developmental psychology is the origin and development of human psychology over the entire life cycle, from conception through birth to maturity and senescence. The term "developmental psychology" in the narrow sense generally refers to individual developmental psychology, which ...
PDF Developmental Psychology and the Biophilia Hypothesis: Children's
developmental psychology. In the ﬁrst section, I sketch some of the promising research that supports the biophilia hypothesis. This task is important, for the idea of biophilia becomes compelling not by any single study, but by the conﬂuence of re-search from diverse ﬁelds. This body of research also sets into motion the
Research in Developmental Psychology
Research in Developmental Psychology What you'll learn to do: examine how to do research in lifespan development. ... In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of ...
Piaget's Theory and Stages of Cognitive Development
Hypothesis Testing Games: Present a scenario and have students come up with hypotheses and ways to test them. Strategy Board Games: Games like chess, checkers, or Settlers of Catan can help in developing strategic and forward-thinking skills. Critical Evaluation Support. The influence of Piaget's ideas on developmental psychology has been ...
Develop A Hypothesis
Developing and focusing your research hypothesis will make putting together your research proposal and project much easier. Do some exploratory research on your broad research idea in your course textbook, class notes, and PsycINFO to identify more specific issues and arguments in your research area and possible relationships between them.
Developmental psychology
Developmental psychology is the scientific study of how and why humans grow, change, and adapt across the course of their lives. Originally concerned with infants and children, ... One hypothesis is that these reflexes are vestigial and have limited use in early human life.
Define Hypothesis: Unveiling the First Step in Scientific Inquiry
Having delved into the concept extensively, we can confidently define a hypothesis as an informed and testable guess or prediction that acts as a guiding light in research studies and scientific investigations. When formulated correctly, it comprises two essential elements: clarity and specificity.
Developmental Psychology Topics
Developmental psychology is a broad topic that involves studying how people grow and change throughout their whole lifetime. Topics don't just include physical growth but also the emotional, cognitive, and social development that people experience at different stages of their lives. ... Have a clear question or hypothesis: Your research ...
Superhero Pretense, Superhero Identification, and Risk-Taking in
Aligning with our hypothesis, descriptive data suggest children with high superhero identification who were randomly assigned to the superhero condition took the most risks among the six subgroups studied (three superhero identification groups by two randomized conditions). ... Journal of Applied Developmental Psychology, 19 (4), 625 ...
Child psychology: Developments in knowledge and theoretical models, Vol. 3
This book discusses the evolution of our knowledge in the field of child psychology over the last 40 years. In a future work, it analyzes the impacts of this evolution on practices and policies in the field of childhood (schooling, health, safety, parenthood). Psychology was for a long time taught in 12th-grade philosophy, tackling various themes such as perception and intelligence, then ...
Male Students in Female-Dominated Study Programs: Perceived Diversity
Psychology as a field of study is more attractive than ever before. For instance, between 2008 and 2018, the number of psychology students in Germany doubled and exceeded 100,000 for the first time in 2020 (Bühner, 2023; Spinath, 2021).Technological developments in recent years have contributed to the increasing number of online and blended learning courses and distance education programs in ...
JCM
Background: Elective soft-tissue-only wrist arthroscopy is a standard procedure in hand surgery for the diagnosis and treatment of wrist pain. A number of pathologies can be treated arthroscopically, with the aim of pain reduction and improved wrist mobility. A postinterventional evaluation of the treatment using objective and patient-reported outcome measures (PROMs) allows for an evidence ...