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Research Design – Types, Methods and Examples

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Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

Providing a clear and concise plan of action for the research study.
Ensuring that the research is conducted ethically and with rigor.
Maximizing the accuracy and reliability of the research findings.
Minimizing the possibility of errors, biases, or confounding variables.
Ensuring that the research is feasible, practical, and cost-effective.
Determining the appropriate research methodology to answer the research question(s).
Identifying the sample size, sampling method, and data collection techniques.
Determining the data analysis method and statistical tests to be used.
Facilitating the replication of the study by other researchers.
Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 3, 2023

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

Data type required for research
Research resources
Participants required for research
Hypothesis based upon research question(s)
Data analysis methodologies
Variables (Independent, dependent, and confounding)
The location and timescale for conducting the data
The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and interpretation techniques. A strong research design reflects a strong dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a dissertation analyzing different situations or cases will have more than one research design.

For example:

Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
Quantitative research is good for the statistical part of the project, but it may not provide an in-depth understanding of the topic .
Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

Do you have enough time to gather data and complete the write-up?
Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
Do you have in-depth knowledge about the different statistical analysis and data collection techniques to address the research questions or test the hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative vs. quantitative data.

Also, see; Research methods, design, and analysis .

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Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results and conclusion .

Read our guidelines to write a research proposal if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The research methodology or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

Research design

The quantitative research design that you set in your dissertation should reflect the type of research questions/hypotheses that you have set. When we talk about quantitative research designs, we are typically referring to research following either a descriptive , experimental , quasi-experimental and relationship-based research design, which we will return to shortly. However, there are also specific goals that you may want to achieve within these research designs. You may want to: (Goal A) explore whether there is a relationship between different variables; (Goal B) predict a score or a membership of a group; or (Goal C) find out the differences between groups you are interested in or treatment conditions that you want to investigate:

GOAL A Exploring the relationship between variables

Are you trying to determine if there is a relationship between two or more variables, and what this relationship is? This kind of design is used to answer questions such as: Is there a relationship between height and basketball performance? Are males more likely to be smokers than females? Does you level of anxiety reduce your exam ability?

GOAL B Predicting a score or a membership of a group

Are you trying to examine whether one variable's value (i.e., the dependent or outcome variable) can be predicted based on another's (i.e., the independent variable). These designs answer questions such as: Can I predict 10km run time based on an individual's aerobic capacity? Can I predict exam anxiety based on knowing the number of hours spent revising? Can I predict whether someone is classified as computer literate based on their performance in different computer tasks? Can I predict an individual's preferred transport (car/motorcycle) based on their response to a risk questionnaire?

GOAL C Testing for differences between groups or treatment conditions

Are you trying to test for differences between groups (e.g., exam performance of males and females) or treatment conditions (e.g., employee turnover among employees (a) given a bonus and (b) not given a bonus)? This type of design aims to answer questions such as: What is the difference in jump height between males and females? Can an exercise-training programme lead to a reduction in blood sugar levels? Do stressed males and females respond differently to different stress-reduction therapies? In each of these cases, we have different groups that we are comparing (e.g., males versus females), and we may also have different treatments (e.g., the example of multiple stress-reduction therapies).

Goals A and B reflect the use of relationship-based research questions/hypotheses, whilst goal C reflects the use of comparative research questions/hypotheses. Just remember that in addition to relating and comparing (i.e., relationship-based and comparative research questions/hypotheses), quantitative research can also be used to describe the phenomena we are interested in (i.e., descriptive research questions). These three basic approaches (i.e., describing , relating and comparing ) can be seen in the following example:

Let's imagine we are interested in examining Facebook usage amongst university students in the United States .

We could describe factors relating to the make-up of these Facebook users, quantifying how many (or what proportion) of these university students were male or female, or what their average age was. We could describe factors relating to their behaviour, such as how frequently they used Facebook each week or the reasons why they joined Facebook in the first place (e.g., to connect with friends, to store all their photos in one place, etc.).

We could compare some of these factors (i.e., those factors that we had just described). For example, we could compare how frequently the students used Facebook each week, looking for differences between male and female students.

We could relate one or more of these factors (e.g., age) to other factors we had examined (e.g., how frequently students used Facebook each week) to find out if there were any associations or relationships between them. For example, we could relate age to how frequently the students used Facebook each week. This could help us discover if there was an association or relationship between these variables (i.e., age and weekly Facebook usage), and if so, tell us something about this association or relationship (e.g., its strength, direction, and/or statistical significance).

These three approaches to examining the constructs you are interested in (i.e., describing , comparing and relating ) are addressed by setting descriptive research questions, and/or comparative or relationship-based research questions/hypotheses. By this stage, you should be very clear about the type of research questions/hypotheses you are addressing, but if you are unsure, refer back to the Research Questions & Hypotheses section of the Fundamentals part of Lærd Dissertation now.

If you are exploring the relationship between variables (i.e., Goal A ), you are likely to be following a relationship-based research design (i.e., a type of non-experimental research design). However, if you are predicting the score or a membership of a group (i.e., Goal B ) or testing for differences between groups or treatment conditions (i.e., Goal C ), you are likely to be following either an experimental or quasi-experimental research design. Unless you already understand the differences between experimental, quasi-experimental and relationship-based research designs, you should read about these different research designs in the Research Designs section of the Fundamentals part of Lærd Dissertation now. You need to do this for two main reasons:

You will have to state which type of research design you are using in your dissertation when writing up the Research Design section of your Chapter Three: Research Strategy .

The research design that you use has a significant influence on your choice of research methods , the research quality of your findings, and even aspects of research ethics that you will have to think about.

Once you are familiar with the four types of research design (i.e., descriptive, experimental, quasi-experimental and relationship-based), you need to think about the route that you are adopting, and the approach within that route in order to set the research design in your dissertation:

ROUTE A: Duplication
ROUTE B: Generalisation
ROUTE C: Extension

Route A: Duplication

If you are taking on Route A: Duplication , you would typically not be expected to make any changes to the research design used in the main journal article when setting the research design for your dissertation. After all, the purpose of the dissertation is duplication , where you are, in effect, re-testing the study in the main journal article to see if the same (or similar) findings are found. An important aspect of such re-testing is typically the use of the same research strategy applied in the main journal article. As such, if an experimental research design was used in the main journal article, with 3 groups (e.g., two treatment groups and one control group), your dissertation would also use an experimental design with the same group characteristics (i.e., 3 groups, with two treatment groups and one control group). The research design you used would also have the same goals as those in the main journal article (e.g., the goal of relating two constructs, perhaps study time and exam performance, in order to answer a relationship-based research question/hypothesis).

However, there are some instances where, from a practical standpoint, you may find that it is not possible to use the same research design, perhaps because an experimental research design was used, but you are unable to randomly selected people from the population you can get access to, forcing you to use a quasi-experimenta l research design. But the goal will be to use the same research design in your dissertation as the one applied in the main journal article. Again, you can learn about the differences between experimental and quasi-experimental designs in the Research Designs section of the Fundamentals part of Lærd Dissertation.

Research Design

Same as research approach, different textbooks place different meanings on research design. Some authors consider research design as the choice between qualitative and quantitative research methods. Others argue that research design refers to the choice of specific methods of data collection and analysis. Research design is also placed as a master plan for conducting a research project and this appears to be the most authentic explanation of the term.

In your dissertation you can define research design as a general plan about what you will do to answer the research question. [1] It is a framework for choosing specific methods of data collection and data analysis.

Research design can be divided into two groups: exploratory and conclusive . Exploratory research, according to its name merely aims to explore specific aspects of the research area. Exploratory research does not aim to provide final and conclusive answers to research questions. The researcher may even change the direction of the study to a certain extent, however not fundamentally, according to new evidences gained during the research process.

Conclusive research, on the contrary, generate findings that can be practically useful for decision-making. The following Table 1 illustrates the main differences between exploratory and conclusive research in relation to important components of a dissertation.

Table 1 Major differences between exploratory and conclusive research design [2]

The following can be mentioned as examples with exploratory design:

A critical analysis of argument of mandatory CSR for UK private sector organisations
A study into contradictions between CSR program and initiatives and business practices: a case study of Philip Morris USA
An investigation into the ways of customer relationship management in mobile marketing environment

Studies listed above do not aim to generate final and conclusive evidences to research questions. These studies merely aim to explore their respective research areas.

Conclusive research can be divided into two categories: descriptive and causal . Descriptive research design, as the name suggests, describes specific elements, causes, or phenomena in the research area.

Table 2 Examples for descriptive research design

Causal research design , on the other hand, is conducted to study cause-and-effect relationships. Table 3 below illustrates some examples for studies with causal research design.

Table 3 Examples for studies with causal design

My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance contains discussions of theory and application of research designs. The e-book also explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy , research approach , methods of data collection , data analysis and sampling are explained in this e-book in simple words.

John Dudovskiy

[1] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th edition, Pearson Education Limited

[2] Source: Pride and Ferrell (2007)

Research Design 101: Research Methods for Students

Which of the many different types of research design is best for you?

One thing that you will want to consider early in your dissertation process is the design of your research study. By the time you start your dissertation or thesis, you have probably taken graduate and undergraduate courses about research methods; however, it has probably been a while since you have taken these courses, and you may need help sorting through all the different types of research design. Below is a brief refresher on different research designs and methodologies.

General Types of Research Designs

Descriptive: Researchers use descriptive research designs to describe particular phenomena or relationships within a single group sample. Descriptive designs are typically used as either pilot or preliminary studies and generally have rather basic statistical procedures. By nature, descriptive studies do not and cannot be used to explain causation.

Descriptive research designs usually provide researchers with information about a group or phenomenon about which there has been little research (e.g., mating patterns of Martians). However, descriptive studies lack randomization and control and cannot be used to determine causation and other implications; in other words, descriptive research designs can only be used to determine “who” and “what,” not “why.”

Quasi-Experimental: Researchers use quasi-experimental research designs to identify differences between two or more groups in an attempt to explain causation. What keeps these types of experiments from being true experiments is lack of randomization. For example, researchers cannot randomly assign gender to participants; therefore, any study in which researchers are investigating differences between genders is inherently quasi-experimental.

Quasi-experimental designs allow researchers more control to make assumptions about causation and implications of findings. Quasi-experimental designs are also useful when researchers want to study particular groups in which group members cannot be randomly assigned (e.g., persons with depression, single mothers, people from different races or ethnic groups, etc.). A major drawback to using quasi-experimental designs is that quasi-experimental research designs typically have less internal validity than do true experimental designs.

Experimental: Experimental research designs have the most control, and, thus, allow researchers to explain differences between groups. One of the key features of an experimental design is that participants are randomly assigned to groups. Experimental designs can be used to test differences between groups (e.g., treatment a group, treatment b group, and control group) or factorial differences within multiple levels of each group (e.g., a drug group [Xanax or Valium] and a psychotherapy group [Cognitive Behavioral Therapy or Rational Emotive Behavioral Therapy]).

True experimental research designs are understood to be the gold standard of research because experimental research designs are the best designs for researchers to predict causation. However, true experimental designs often require more resources than do other research designs and will not work with all research questions.

Specific Types of Research Designs

Single-Sample Repeated Measures: A design method in which the same group is tested at multiple points in time. Giving students an assessment of knowledge the first day of class and giving the same assessment on the last day of class is an example of a research design based on a single-sample repeated measures.

ABA: A specific single-sample repeated measures design in which participants are measured at baseline (A), after an intervention (B), and again after the intervention has been removed (A).

Between Groups: A design in which researchers compare the scores of two or more groups. Between-group designs can be used as either a single or repeated measure.

Matched Sample: A specific between-groups design in which researchers match participants across groups based on criteria determined by the researchers (e.g., age, IQ, gender, etc.). After matching participants based on the predetermined criteria, researchers examine differences between matched pairs (not between group means).

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Research Design: What it is, Elements & Types

Can you imagine doing research without a plan? Probably not. When we discuss a strategy to collect, study, and evaluate data, we talk about research design. This design addresses problems and creates a consistent and logical model for data analysis. Let’s learn more about it.

What is Research Design?

Research design is the framework of research methods and techniques chosen by a researcher to conduct a study. The design allows researchers to sharpen the research methods suitable for the subject matter and set up their studies for success.

Creating a research topic explains the type of research (experimental, survey research , correlational , semi-experimental, review) and its sub-type (experimental design, research problem , descriptive case-study).

There are three main types of designs for research:

Data collection
Measurement
Data Analysis

The research problem an organization faces will determine the design, not vice-versa. The design phase of a study determines which tools to use and how they are used.

The Process of Research Design

The research design process is a systematic and structured approach to conducting research. The process is essential to ensure that the study is valid, reliable, and produces meaningful results.

Consider your aims and approaches: Determine the research questions and objectives, and identify the theoretical framework and methodology for the study.
Choose a type of Research Design: Select the appropriate research design, such as experimental, correlational, survey, case study, or ethnographic, based on the research questions and objectives.
Identify your population and sampling method: Determine the target population and sample size, and choose the sampling method, such as random , stratified random sampling , or convenience sampling.
Choose your data collection methods: Decide on the methods, such as surveys, interviews, observations, or experiments, and select the appropriate instruments or tools for collecting data.
Plan your data collection procedures: Develop a plan for data collection, including the timeframe, location, and personnel involved, and ensure ethical considerations.
Decide on your data analysis strategies: Select the appropriate data analysis techniques, such as statistical analysis , content analysis, or discourse analysis, and plan how to interpret the results.

The process of research design is a critical step in conducting research. By following the steps of research design, researchers can ensure that their study is well-planned, ethical, and rigorous.

Research Design Elements

Impactful research usually creates a minimum bias in data and increases trust in the accuracy of collected data. A design that produces the slightest margin of error in experimental research is generally considered the desired outcome. The essential elements are:

Accurate purpose statement
Techniques to be implemented for collecting and analyzing research
The method applied for analyzing collected details
Type of research methodology
Probable objections to research
Settings for the research study
Measurement of analysis

Characteristics of Research Design

A proper design sets your study up for success. Successful research studies provide insights that are accurate and unbiased. You’ll need to create a survey that meets all of the main characteristics of a design. There are four key characteristics:

Neutrality: When you set up your study, you may have to make assumptions about the data you expect to collect. The results projected in the research should be free from research bias and neutral. Understand opinions about the final evaluated scores and conclusions from multiple individuals and consider those who agree with the results.
Reliability: With regularly conducted research, the researcher expects similar results every time. You’ll only be able to reach the desired results if your design is reliable. Your plan should indicate how to form research questions to ensure the standard of results.
Validity: There are multiple measuring tools available. However, the only correct measuring tools are those which help a researcher in gauging results according to the objective of the research. The questionnaire developed from this design will then be valid.
Generalization: The outcome of your design should apply to a population and not just a restricted sample . A generalized method implies that your survey can be conducted on any part of a population with similar accuracy.

The above factors affect how respondents answer the research questions, so they should balance all the above characteristics in a good design. If you want, you can also learn about Selection Bias through our blog.

Research Design Types

A researcher must clearly understand the various types to select which model to implement for a study. Like the research itself, the design of your analysis can be broadly classified into quantitative and qualitative.

Qualitative research

Qualitative research determines relationships between collected data and observations based on mathematical calculations. Statistical methods can prove or disprove theories related to a naturally existing phenomenon. Researchers rely on qualitative observation research methods that conclude “why” a particular theory exists and “what” respondents have to say about it.

Quantitative research

Quantitative research is for cases where statistical conclusions to collect actionable insights are essential. Numbers provide a better perspective for making critical business decisions. Quantitative research methods are necessary for the growth of any organization. Insights drawn from complex numerical data and analysis prove to be highly effective when making decisions about the business’s future.

Qualitative Research vs Quantitative Research

Here is a chart that highlights the major differences between qualitative and quantitative research:

In summary or analysis , the step of qualitative research is more exploratory and focuses on understanding the subjective experiences of individuals, while quantitative research is more focused on objective data and statistical analysis.

You can further break down the types of research design into five categories:

1. Descriptive: In a descriptive composition, a researcher is solely interested in describing the situation or case under their research study. It is a theory-based design method created by gathering, analyzing, and presenting collected data. This allows a researcher to provide insights into the why and how of research. Descriptive design helps others better understand the need for the research. If the problem statement is not clear, you can conduct exploratory research.

2. Experimental: Experimental research establishes a relationship between the cause and effect of a situation. It is a causal research design where one observes the impact caused by the independent variable on the dependent variable. For example, one monitors the influence of an independent variable such as a price on a dependent variable such as customer satisfaction or brand loyalty. It is an efficient research method as it contributes to solving a problem.

The independent variables are manipulated to monitor the change it has on the dependent variable. Social sciences often use it to observe human behavior by analyzing two groups. Researchers can have participants change their actions and study how the people around them react to understand social psychology better.

3. Correlational research: Correlational research is a non-experimental research technique. It helps researchers establish a relationship between two closely connected variables. There is no assumption while evaluating a relationship between two other variables, and statistical analysis techniques calculate the relationship between them. This type of research requires two different groups.

A correlation coefficient determines the correlation between two variables whose values range between -1 and +1. If the correlation coefficient is towards +1, it indicates a positive relationship between the variables, and -1 means a negative relationship between the two variables.

4. Diagnostic research: In diagnostic design, the researcher is looking to evaluate the underlying cause of a specific topic or phenomenon. This method helps one learn more about the factors that create troublesome situations.

This design has three parts of the research:

Inception of the issue
Diagnosis of the issue
Solution for the issue

5. Explanatory research : Explanatory design uses a researcher’s ideas and thoughts on a subject to further explore their theories. The study explains unexplored aspects of a subject and details the research questions’ what, how, and why.

Benefits of Research Design

There are several benefits of having a well-designed research plan. Including:

Clarity of research objectives: Research design provides a clear understanding of the research objectives and the desired outcomes.
Increased validity and reliability: To ensure the validity and reliability of results, research design help to minimize the risk of bias and helps to control extraneous variables.
Improved data collection: Research design helps to ensure that the proper data is collected and data is collected systematically and consistently.
Better data analysis: Research design helps ensure that the collected data can be analyzed effectively, providing meaningful insights and conclusions.
Improved communication: A well-designed research helps ensure the results are clean and influential within the research team and external stakeholders.
Efficient use of resources: reducing the risk of waste and maximizing the impact of the research, research design helps to ensure that resources are used efficiently.

A well-designed research plan is essential for successful research, providing clear and meaningful insights and ensuring that resources are practical.

QuestionPro offers a comprehensive solution for researchers looking to conduct research. With its user-friendly interface, robust data collection and analysis tools, and the ability to integrate results from multiple sources, QuestionPro provides a versatile platform for designing and executing research projects.

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USC Libraries
Research Guides

Organizing Your Social Sciences Research Paper

Types of Research Designs
Purpose of Guide
Design Flaws to Avoid
Independent and Dependent Variables
Glossary of Research Terms
Reading Research Effectively
Narrowing a Topic Idea
Broadening a Topic Idea
Extending the Timeliness of a Topic Idea
Academic Writing Style
Applying Critical Thinking
Choosing a Title
Making an Outline
Paragraph Development
Research Process Video Series
Executive Summary
The C.A.R.S. Model
Background Information
The Research Problem/Question
Theoretical Framework
Citation Tracking
Content Alert Services
Evaluating Sources
Primary Sources
Secondary Sources
Tiertiary Sources
Scholarly vs. Popular Publications
Qualitative Methods
Quantitative Methods
Insiderness
Using Non-Textual Elements
Limitations of the Study
Common Grammar Mistakes
Writing Concisely
Avoiding Plagiarism
Footnotes or Endnotes?
Further Readings
Generative AI and Writing
USC Libraries Tutorials and Other Guides
Bibliography

Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
Review and synthesize previously published literature associated with the research problem,
Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE : Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

This is a collaborative and adaptive research design that lends itself to use in work or community situations.
Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
Action research studies often have direct and obvious relevance to improving practice and advocating for change.
There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
Personal over-involvement of the researcher may bias research results.
The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA: Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
Design can extend experience or add strength to what is already known through previous research.
Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
The design can provide detailed descriptions of specific and rare cases.
A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
Design does not facilitate assessment of cause and effect relationships.
Vital information may be missing, making the case hard to interpret.
The case may not be representative or typical of the larger problem being investigated.
If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
Replication is possible.
There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
Either original data or secondary data can be used in this design.
In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
Studies cannot be utilized to establish cause and effect relationships.
This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
If the limitations are understood, they can be a useful tool in developing a more focused study.
Descriptive studies can yield rich data that lead to important recommendations in practice.
Appoach collects a large amount of data for detailed analysis.
The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
Approach provides the highest level of evidence for single studies.
The design is artificial, and results may not generalize well to the real world.
The artificial settings of experiments may alter the behaviors or responses of participants.
Experimental designs can be costly if special equipment or facilities are needed.
Some research problems cannot be studied using an experiment because of ethical or technical reasons.
Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

Familiarity with basic details, settings, and concerns.
Well grounded picture of the situation being developed.
Generation of new ideas and assumptions.
Development of tentative theories or hypotheses.
Determination about whether a study is feasible in the future.
Issues get refined for more systematic investigation and formulation of new research questions.
Direction for future research and techniques get developed.
Design is a useful approach for gaining background information on a particular topic.
Exploratory research is flexible and can address research questions of all types (what, why, how).
Provides an opportunity to define new terms and clarify existing concepts.
Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field [i.e., the act of triangulating the data].
Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

The historical research design is unobtrusive; the act of research does not affect the results of the study.
The historical approach is well suited for trend analysis.
Historical records can add important contextual background required to more fully understand and interpret a research problem.
There is often no possibility of researcher-subject interaction that could affect the findings.
Historical sources can be used over and over to study different research problems or to replicate a previous study.
The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
Interpreting historical sources can be very time consuming.
The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58; Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
The data collection method may change over time.
Maintaining the integrity of the original sample can be difficult over an extended period of time.
It can be difficult to show more than one variable at a time.
This design often needs qualitative research data to explain fluctuations in the results.
A longitudinal research design assumes present trends will continue unchanged.
It can take a long period of time to gather results.
There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
A well-reasoned and well-documented justification for identification and selection of the studies;
Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
Justification of the techniques used to evaluate the studies.
Can be an effective strategy for determining gaps in the literature.
Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
Can be used to generate new hypotheses or highlight research problems for future studies.
Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
A large sample size can yield reliable, but not necessarily valid, results.
A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
The strengths of one method can be used to overcome the inherent weaknesses of another method.
Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
The researcher is able to collect in-depth information about a particular behavior.
Can reveal interrelationships among multifaceted dimensions of group interactions.
You can generalize your results to real life situations.
Observational research is useful for discovering what variables may be important before applying other methods like experiments.
Observation research designs account for the complexity of group behaviors.
Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
There can be problems with bias as the researcher may only "see what they want to see."
There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
Sources or subjects may not all be equally credible.
Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
Can provide a basis for applying ethical decision-making to practice.
Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
Brings clarity to general guiding practices and principles of an individual or group.
Philosophy informs methodology.
Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
Limited application to specific research problems [answering the "So What?" question in social science research].
Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
There are limitations in the use of metaphor as a vehicle of philosophical analysis.
There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

The researcher has a limitless option when it comes to sample size and the sampling schedule.
Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
This is a useful design for exploratory studies.
There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods . David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research." Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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What is a Research Design? Definition, Types, Methods and Examples

By Nick Jain

Published on: September 8, 2023

Table of Contents

What is a Research Design?

12 types of research design, top 16 research design methods, research design examples.

A research design is defined as the overall plan or structure that guides the process of conducting research. It is a critical component of the research process and serves as a blueprint for how a study will be carried out, including the methods and techniques that will be used to collect and analyze data. A well-designed research study is essential for ensuring that the research objectives are met and that the results are valid and reliable.

Key elements of research design include:

Research Objectives: Clearly define the goals and objectives of the research study. What is the research trying to achieve or investigate?
Research Questions or Hypotheses: Formulating specific research questions or hypotheses that address the objectives of the study. These questions guide the research process.
Data Collection Methods: Determining how data will be collected, whether through surveys, experiments, observations, interviews, archival research, or a combination of these methods.
Sampling: Deciding on the target population and selecting a sample that represents that population. Sampling methods can vary, such as random sampling, stratified sampling, or convenience sampling.
Data Collection Instruments: Developing or selecting the tools and instruments needed to collect data, such as questionnaires, surveys, or experimental equipment.
Data Analysis: Defining the statistical or analytical techniques that will be used to analyze the collected data. This may involve qualitative or quantitative methods , depending on the research goals.
Time Frame: Establishing a timeline for the research project, including when data will be collected, analyzed, and reported.
Ethical Considerations: Addressing ethical issues, including obtaining informed consent from participants, ensuring the privacy and confidentiality of data, and adhering to ethical guidelines.
Resources: Identifying the resources needed for the research , including funding, personnel, equipment, and access to data sources.
Data Presentation and Reporting: Planning how the research findings will be presented and reported, whether through written reports, presentations, or other formats.

There are various research designs, such as experimental, observational, survey, case study, and longitudinal designs, each suited to different research questions and objectives. The choice of research design depends on the nature of the research and the goals of the study.

A well-constructed research design is crucial because it helps ensure the validity, reliability, and generalizability of research findings, allowing researchers to draw meaningful conclusions and contribute to the body of knowledge in their field.

Understanding the nuances of research design is pivotal in steering your investigation towards success. Delving into various research designs empowers researchers to craft tailored methodologies to address specific queries and attain precise objectives. Here, we unveil a spectrum of research designs, meticulously curated to cater to diverse research pursuits.

1. Experimental Research Design

Randomized Controlled Trial (RCT): Immerse yourself in the realm of experimentation with RCTs. Randomly assigning individuals to either an experimental or control group enables meticulous assessment of interventions or treatments’ efficacy.

2. Quasi-Experimental Research Design

Non-equivalent Group Design: When randomness isn’t viable, non-equivalent group designs offer a pragmatic alternative. Comparison across multiple groups without random assignment ensures ethical and feasible research conduct.

3. Observational Research Design

Cross-Sectional Study: Capture snapshots of data at a single moment with cross-sectional studies, unraveling intricate relationships and disparities between variables.

Longitudinal Study: Embark on a journey through time with longitudinal studies, tracking participants’ trajectories to discern evolving trends and patterns.

4. Descriptive Research Design

Survey Research: Dive into the depths of data collection through surveys, extracting insights into attitudes, characteristics, and opinions.

Case Study: Engage in profound exploration through case studies, dissecting singular individuals, groups, or phenomena to unravel profound insights.

5. Correlational Research Design

Correlational Study: Traverse the realm of correlations, scrutinizing interrelationships between variables while refraining from inferring causality.

6. Ex Post Facto Research Design

Retrospective Exploration: Explore existing conditions and behaviors retrospectively, shedding light on potential causes where variable manipulation isn’t feasible.

7. Exploratory Research Design

Pilot Study: Initiate your research odyssey with pilot studies, laying the groundwork for comprehensive investigations while refining research procedures.

8. Cohort Study

Chronicle of Evolution: Embark on longitudinal expeditions with cohort studies, monitoring cohorts to elucidate the evolution of specific outcomes over time.

9. Action Research

Driving Change: Collaboratively navigate practical challenges with action research, fostering improvements in educational or organizational settings.

10. Meta-Analysis

Synthesizing Insights: Merge insights from multiple studies with meta-analyses, presenting a holistic overview of research findings.

11. Cross-Sequential Design

Bridging the Gap: Seamlessly blend cross-sectional and longitudinal elements to dissect age-related changes across diverse cohorts.

12. Grounded Theory

Rooted Insights: Plunge into the depths of qualitative research with grounded theory, crafting theories grounded in meticulously collected data.

Selecting the optimal research design is akin to sculpting a masterpiece, contingent on the intricacies of the research query, resource availability, ethical considerations, and the desired data intricacies. Researchers adeptly navigate these choices to seamlessly align their methodologies with their research ambitions, ensuring both precision and impact.

Learn more: What is Research?

Research design methods refer to the systematic approaches and techniques used to plan, structure, and conduct a research study. The choice of research design method depends on the research questions, objectives, and the nature of the study. Here are some key research design methods commonly used in various fields:

1. Experimental Method

Controlled Experiments: In controlled experiments, researchers manipulate one or more independent variables and measure their effects on dependent variables while controlling for confounding factors.

2. Observational Method

Naturalistic Observation: Researchers observe and record behavior in its natural setting without intervening. This method is often used in psychology and anthropology.

Structured Observation: Observations are made using a predetermined set of criteria or a structured observation schedule.

3. Survey Method

Questionnaires: Researchers collect data by administering structured questionnaires to participants. This method is widely used for collecting quantitative research data.

Interviews: In interviews, researchers ask questions directly to participants, allowing for more in-depth responses. Interviews can take on structured, semi-structured, or unstructured formats.

4. Case Study Method

Single-Case Study: Focuses on a single individual or entity, providing an in-depth analysis of that case.

Multiple-Case Study: Involves the examination of multiple cases to identify patterns, commonalities, or differences.

5. Content Analysis

Researchers analyze textual, visual, or audio data to identify patterns, themes, and trends. This method is commonly used in media studies and social sciences.

6. Historical Research

Researchers examine historical documents, records, and artifacts to understand past events, trends, and contexts.

7. Action Research

Researchers work collaboratively with practitioners to address practical problems or implement interventions in real-world settings.

8. Ethnographic Research

Researchers immerse themselves in a particular cultural or social group to gain a deep understanding of their behaviors, beliefs, and practices.

9. Cross-sectional and Longitudinal Surveys

Cross-sectional surveys collect data from a sample of participants at a single point in time.

Longitudinal surveys collect data from the same participants over an extended period, allowing for the study of changes over time.

Researchers conduct a quantitative synthesis of data from multiple studies to provide a comprehensive overview of research findings on a particular topic.

11. Mixed-Methods Research

Combines qualitative and quantitative research methods to provide a more holistic understanding of a research problem.

A qualitative research method that aims to develop theories or explanations grounded in the data collected during the research process.

13. Simulation and Modeling

Researchers use mathematical or computational models to simulate real-world phenomena and explore various scenarios.

14. Survey Experiments

Combines elements of surveys and experiments, allowing researchers to manipulate variables within a survey context.

15. Case-Control Studies and Cohort Studies

These epidemiological research methods are used to study the causes and risk factors associated with diseases and health outcomes.

16. Cross-Sequential Design

Combines elements of cross-sectional and longitudinal research to examine both age-related changes and cohort differences.

The selection of a specific research design method should align with the research objectives, the type of data needed, available resources, ethical considerations, and the overall research approach. Researchers often choose methods that best suit the nature of their study and research questions to ensure that they collect relevant and valid data.

Learn more: What is Research Objective?

Research designs can vary significantly depending on the research questions and objectives. Here are some examples of research designs across different disciplines:

Experimental Design: A pharmaceutical company conducts a randomized controlled trial (RCT) to test the efficacy of a new drug. Participants are randomly assigned to two groups: one receiving the new drug and the other a placebo. The company measures the health outcomes of both groups over a specific period.
Observational Design: An ecologist observes the behavior of a particular bird species in its natural habitat to understand its feeding patterns, mating rituals, and migration habits.
Survey Design: A market research firm conducts a survey to gather data on consumer preferences for a new product. They distribute a questionnaire to a representative sample of the target population and analyze the responses.
Case Study Design: A psychologist conducts a case study on an individual with a rare psychological disorder to gain insights into the causes, symptoms, and potential treatments of the condition.
Content Analysis: Researchers analyze a large dataset of social media posts to identify trends in public opinion and sentiment during a political election campaign.
Historical Research: A historian examines primary sources such as letters, diaries, and official documents to reconstruct the events and circumstances leading up to a significant historical event.
Action Research: A school teacher collaborates with colleagues to implement a new teaching method in their classrooms and assess its impact on student learning outcomes through continuous reflection and adjustment.
Ethnographic Research: An anthropologist lives with and observes an indigenous community for an extended period to understand their culture, social structures, and daily lives.
Cross-Sectional Survey: A public health agency conducts a cross-sectional survey to assess the prevalence of smoking among different age groups in a specific region during a particular year.
Longitudinal Study: A developmental psychologist follows a group of children from infancy through adolescence to study their cognitive, emotional, and social development over time.
Meta-Analysis: Researchers aggregate and analyze the results of multiple studies on the effectiveness of a specific type of therapy to provide a comprehensive overview of its outcomes.
Mixed-Methods Research: A sociologist combines surveys and in-depth interviews to study the impact of a community development program on residents’ quality of life.
Grounded Theory: A sociologist conducts interviews with homeless individuals to develop a theory explaining the factors that contribute to homelessness and the strategies they use to cope.
Simulation and Modeling: Climate scientists use computer models to simulate the effects of various greenhouse gas emission scenarios on global temperatures and sea levels.
Case-Control Study: Epidemiologists investigate a disease outbreak by comparing a group of individuals who contracted the disease (cases) with a group of individuals who did not (controls) to identify potential risk factors.

These examples demonstrate the diversity of research designs used in different fields to address a wide range of research questions and objectives. Researchers select the most appropriate design based on the specific context and goals of their study.

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Research Process

What is Research Design?

Some definitions.

Types of Information
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Research design is a "design or strategy that justifies the logic, structure and the principles of the research methodology and methods and how these relate to the research questions, hypothesis or proposition." The research design best suited to your project can be influenced by your discipline, topic, existing research, and availability.

Davies, P. (2006). Research design. In V. Jupp (Ed.), The SAGE dictionary of social research methods. (pp. 266-267). London, England: SAGE Publications, Ltd.

Use the links below to learn more about the different types of research design: Qualitative Research Guide Quantitative Research Guide

Dissertation A requirement of a doctoral degree candidate containing research and criticism or analysis which displays originality. In most cases, a professor or faculty member serve as an advisor, or committee chair, to the candidate. There are often three steps to completing the dissertation: Proposal, activation and presentation and approval.

Krathwohl, D. (2010). Dissertation. In N. Salkind (Ed.), Encyclopedia of Research Design. (pp. 377-380). Thousand Oaks, CA: SAGE Publications, Inc. doi:10.4135/9781412961288.n118

Mixed Method Design Research design that includes both qualitative and quantitative methods. This may be necessary in order to best approach a research question or acheive better results by expanding the scope of the research. The methods used in research design should include the following: "(a) the relationship between the researcher and research “subjects,” (b) details of the experimental environment (place, time, etc.), (c) sampling and data collection methods, (d) data analysis strategies, and (e) knowledge dissemination."

Pinto, R. (2010). Mixed Methods Design. In N. Salkind (Ed.), Encyclopedia of Research Design . (pp. 813-819). Thousand Oaks, CA: SAGE Publications, Inc. doi:10.4135/9781412961288.n245

Program Evaluation A process designed to determine the the worth, value or significance of a program which combines both "knowledge and action" (Kushner, 2005, p. 335).The process and results of a program evaluation can be seen as an asset itself.

Kushner, S. (2005). Program Evaluation. In S. Mathison (Ed.), Encyclopedia of Evaluation . (pp. 335-340). Thousand Oaks, CA: SAGE Publications, Inc. doi:10.4135/9781412950558.n445

Qualitative Research Research design that uses empirical, not numerical, data. The method of data collection should be appropriate to the discipline and ensure that the data is comprehensible after collection.

What is qualitative research? (2007). In U. Flick (Ed.), Designing Qualitative Research . (pp. 2-16). London, England: SAGE Publications, Ltd. doi:10.4135/9781849208826.n1

Quantitative Research Research design that produces data that can be used to illustrate numerical or measureable properties of a population or situation that may be able to explain or predict.

Kraska, M. (2010). Quantitative Research. In N. Salkind (Ed.), Encyclopedia of Research Design . (pp. 1167-1172). Thousand Oaks, CA: SAGE Publications, Inc. doi:10.4135/9781412961288.n352

Test, Instrument, Measurement or Survey Methods of gathering metrics related to the originial research component for a dissertation. For more information about these tools, check out this guide .

Thesis Literally, "a statement or theory that is put forward as a premise to be maintained or proved." In academic usage, it is written work by a candidate for a university degree, usually at the Master's level.

Thesis. (2010). In Stevenson, A. (Ed.), Oxford English dictionary of English (3rd ed.). doi:10.1093/acref/9780199571123.001.0001

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Chapter 2. Research Design

Getting started.

When I teach undergraduates qualitative research methods, the final product of the course is a “research proposal” that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question. I highly recommend you think about designing your own research study as you progress through this textbook. Even if you don’t have a study in mind yet, it can be a helpful exercise as you progress through the course. But how to start? How can one design a research study before they even know what research looks like? This chapter will serve as a brief overview of the research design process to orient you to what will be coming in later chapters. Think of it as a “skeleton” of what you will read in more detail in later chapters. Ideally, you will read this chapter both now (in sequence) and later during your reading of the remainder of the text. Do not worry if you have questions the first time you read this chapter. Many things will become clearer as the text advances and as you gain a deeper understanding of all the components of good qualitative research. This is just a preliminary map to get you on the right road.

Research Design Steps

Before you even get started, you will need to have a broad topic of interest in mind. [1] . In my experience, students can confuse this broad topic with the actual research question, so it is important to clearly distinguish the two. And the place to start is the broad topic. It might be, as was the case with me, working-class college students. But what about working-class college students? What’s it like to be one? Why are there so few compared to others? How do colleges assist (or fail to assist) them? What interested me was something I could barely articulate at first and went something like this: “Why was it so difficult and lonely to be me?” And by extension, “Did others share this experience?”

Once you have a general topic, reflect on why this is important to you. Sometimes we connect with a topic and we don’t really know why. Even if you are not willing to share the real underlying reason you are interested in a topic, it is important that you know the deeper reasons that motivate you. Otherwise, it is quite possible that at some point during the research, you will find yourself turned around facing the wrong direction. I have seen it happen many times. The reason is that the research question is not the same thing as the general topic of interest, and if you don’t know the reasons for your interest, you are likely to design a study answering a research question that is beside the point—to you, at least. And this means you will be much less motivated to carry your research to completion.

Researcher Note

Why do you employ qualitative research methods in your area of study? What are the advantages of qualitative research methods for studying mentorship?

Qualitative research methods are a huge opportunity to increase access, equity, inclusion, and social justice. Qualitative research allows us to engage and examine the uniquenesses/nuances within minoritized and dominant identities and our experiences with these identities. Qualitative research allows us to explore a specific topic, and through that exploration, we can link history to experiences and look for patterns or offer up a unique phenomenon. There’s such beauty in being able to tell a particular story, and qualitative research is a great mode for that! For our work, we examined the relationships we typically use the term mentorship for but didn’t feel that was quite the right word. Qualitative research allowed us to pick apart what we did and how we engaged in our relationships, which then allowed us to more accurately describe what was unique about our mentorship relationships, which we ultimately named liberationships ( McAloney and Long 2021) . Qualitative research gave us the means to explore, process, and name our experiences; what a powerful tool!

How do you come up with ideas for what to study (and how to study it)? Where did you get the idea for studying mentorship?

Coming up with ideas for research, for me, is kind of like Googling a question I have, not finding enough information, and then deciding to dig a little deeper to get the answer. The idea to study mentorship actually came up in conversation with my mentorship triad. We were talking in one of our meetings about our relationship—kind of meta, huh? We discussed how we felt that mentorship was not quite the right term for the relationships we had built. One of us asked what was different about our relationships and mentorship. This all happened when I was taking an ethnography course. During the next session of class, we were discussing auto- and duoethnography, and it hit me—let’s explore our version of mentorship, which we later went on to name liberationships ( McAloney and Long 2021 ). The idea and questions came out of being curious and wanting to find an answer. As I continue to research, I see opportunities in questions I have about my work or during conversations that, in our search for answers, end up exposing gaps in the literature. If I can’t find the answer already out there, I can study it.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

When you have a better idea of why you are interested in what it is that interests you, you may be surprised to learn that the obvious approaches to the topic are not the only ones. For example, let’s say you think you are interested in preserving coastal wildlife. And as a social scientist, you are interested in policies and practices that affect the long-term viability of coastal wildlife, especially around fishing communities. It would be natural then to consider designing a research study around fishing communities and how they manage their ecosystems. But when you really think about it, you realize that what interests you the most is how people whose livelihoods depend on a particular resource act in ways that deplete that resource. Or, even deeper, you contemplate the puzzle, “How do people justify actions that damage their surroundings?” Now, there are many ways to design a study that gets at that broader question, and not all of them are about fishing communities, although that is certainly one way to go. Maybe you could design an interview-based study that includes and compares loggers, fishers, and desert golfers (those who golf in arid lands that require a great deal of wasteful irrigation). Or design a case study around one particular example where resources were completely used up by a community. Without knowing what it is you are really interested in, what motivates your interest in a surface phenomenon, you are unlikely to come up with the appropriate research design.

These first stages of research design are often the most difficult, but have patience . Taking the time to consider why you are going to go through a lot of trouble to get answers will prevent a lot of wasted energy in the future.

There are distinct reasons for pursuing particular research questions, and it is helpful to distinguish between them. First, you may be personally motivated. This is probably the most important and the most often overlooked. What is it about the social world that sparks your curiosity? What bothers you? What answers do you need in order to keep living? For me, I knew I needed to get a handle on what higher education was for before I kept going at it. I needed to understand why I felt so different from my peers and whether this whole “higher education” thing was “for the likes of me” before I could complete my degree. That is the personal motivation question. Your personal motivation might also be political in nature, in that you want to change the world in a particular way. It’s all right to acknowledge this. In fact, it is better to acknowledge it than to hide it.

There are also academic and professional motivations for a particular study. If you are an absolute beginner, these may be difficult to find. We’ll talk more about this when we discuss reviewing the literature. Simply put, you are probably not the only person in the world to have thought about this question or issue and those related to it. So how does your interest area fit into what others have studied? Perhaps there is a good study out there of fishing communities, but no one has quite asked the “justification” question. You are motivated to address this to “fill the gap” in our collective knowledge. And maybe you are really not at all sure of what interests you, but you do know that [insert your topic] interests a lot of people, so you would like to work in this area too. You want to be involved in the academic conversation. That is a professional motivation and a very important one to articulate.

Practical and strategic motivations are a third kind. Perhaps you want to encourage people to take better care of the natural resources around them. If this is also part of your motivation, you will want to design your research project in a way that might have an impact on how people behave in the future. There are many ways to do this, one of which is using qualitative research methods rather than quantitative research methods, as the findings of qualitative research are often easier to communicate to a broader audience than the results of quantitative research. You might even be able to engage the community you are studying in the collecting and analyzing of data, something taboo in quantitative research but actively embraced and encouraged by qualitative researchers. But there are other practical reasons, such as getting “done” with your research in a certain amount of time or having access (or no access) to certain information. There is nothing wrong with considering constraints and opportunities when designing your study. Or maybe one of the practical or strategic goals is about learning competence in this area so that you can demonstrate the ability to conduct interviews and focus groups with future employers. Keeping that in mind will help shape your study and prevent you from getting sidetracked using a technique that you are less invested in learning about.

STOP HERE for a moment

I recommend you write a paragraph (at least) explaining your aims and goals. Include a sentence about each of the following: personal/political goals, practical or professional/academic goals, and practical/strategic goals. Think through how all of the goals are related and can be achieved by this particular research study . If they can’t, have a rethink. Perhaps this is not the best way to go about it.

You will also want to be clear about the purpose of your study. “Wait, didn’t we just do this?” you might ask. No! Your goals are not the same as the purpose of the study, although they are related. You can think about purpose lying on a continuum from “ theory ” to “action” (figure 2.1). Sometimes you are doing research to discover new knowledge about the world, while other times you are doing a study because you want to measure an impact or make a difference in the world.

Purpose types: Basic Research, Applied Research, Summative Evaluation, Formative Evaluation, Action Research

Basic research involves research that is done for the sake of “pure” knowledge—that is, knowledge that, at least at this moment in time, may not have any apparent use or application. Often, and this is very important, knowledge of this kind is later found to be extremely helpful in solving problems. So one way of thinking about basic research is that it is knowledge for which no use is yet known but will probably one day prove to be extremely useful. If you are doing basic research, you do not need to argue its usefulness, as the whole point is that we just don’t know yet what this might be.

Researchers engaged in basic research want to understand how the world operates. They are interested in investigating a phenomenon to get at the nature of reality with regard to that phenomenon. The basic researcher’s purpose is to understand and explain ( Patton 2002:215 ).

Basic research is interested in generating and testing hypotheses about how the world works. Grounded Theory is one approach to qualitative research methods that exemplifies basic research (see chapter 4). Most academic journal articles publish basic research findings. If you are working in academia (e.g., writing your dissertation), the default expectation is that you are conducting basic research.

Applied research in the social sciences is research that addresses human and social problems. Unlike basic research, the researcher has expectations that the research will help contribute to resolving a problem, if only by identifying its contours, history, or context. From my experience, most students have this as their baseline assumption about research. Why do a study if not to make things better? But this is a common mistake. Students and their committee members are often working with default assumptions here—the former thinking about applied research as their purpose, the latter thinking about basic research: “The purpose of applied research is to contribute knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment. While in basic research the source of questions is the tradition within a scholarly discipline, in applied research the source of questions is in the problems and concerns experienced by people and by policymakers” ( Patton 2002:217 ).

Applied research is less geared toward theory in two ways. First, its questions do not derive from previous literature. For this reason, applied research studies have much more limited literature reviews than those found in basic research (although they make up for this by having much more “background” about the problem). Second, it does not generate theory in the same way as basic research does. The findings of an applied research project may not be generalizable beyond the boundaries of this particular problem or context. The findings are more limited. They are useful now but may be less useful later. This is why basic research remains the default “gold standard” of academic research.

Evaluation research is research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems. We already know the problems, and someone has already come up with solutions. There might be a program, say, for first-generation college students on your campus. Does this program work? Are first-generation students who participate in the program more likely to graduate than those who do not? These are the types of questions addressed by evaluation research. There are two types of research within this broader frame; however, one more action-oriented than the next. In summative evaluation , an overall judgment about the effectiveness of a program or policy is made. Should we continue our first-gen program? Is it a good model for other campuses? Because the purpose of such summative evaluation is to measure success and to determine whether this success is scalable (capable of being generalized beyond the specific case), quantitative data is more often used than qualitative data. In our example, we might have “outcomes” data for thousands of students, and we might run various tests to determine if the better outcomes of those in the program are statistically significant so that we can generalize the findings and recommend similar programs elsewhere. Qualitative data in the form of focus groups or interviews can then be used for illustrative purposes, providing more depth to the quantitative analyses. In contrast, formative evaluation attempts to improve a program or policy (to help “form” or shape its effectiveness). Formative evaluations rely more heavily on qualitative data—case studies, interviews, focus groups. The findings are meant not to generalize beyond the particular but to improve this program. If you are a student seeking to improve your qualitative research skills and you do not care about generating basic research, formative evaluation studies might be an attractive option for you to pursue, as there are always local programs that need evaluation and suggestions for improvement. Again, be very clear about your purpose when talking through your research proposal with your committee.

Action research takes a further step beyond evaluation, even formative evaluation, to being part of the solution itself. This is about as far from basic research as one could get and definitely falls beyond the scope of “science,” as conventionally defined. The distinction between action and research is blurry, the research methods are often in constant flux, and the only “findings” are specific to the problem or case at hand and often are findings about the process of intervention itself. Rather than evaluate a program as a whole, action research often seeks to change and improve some particular aspect that may not be working—maybe there is not enough diversity in an organization or maybe women’s voices are muted during meetings and the organization wonders why and would like to change this. In a further step, participatory action research , those women would become part of the research team, attempting to amplify their voices in the organization through participation in the action research. As action research employs methods that involve people in the process, focus groups are quite common.

If you are working on a thesis or dissertation, chances are your committee will expect you to be contributing to fundamental knowledge and theory ( basic research ). If your interests lie more toward the action end of the continuum, however, it is helpful to talk to your committee about this before you get started. Knowing your purpose in advance will help avoid misunderstandings during the later stages of the research process!

The Research Question

Once you have written your paragraph and clarified your purpose and truly know that this study is the best study for you to be doing right now , you are ready to write and refine your actual research question. Know that research questions are often moving targets in qualitative research, that they can be refined up to the very end of data collection and analysis. But you do have to have a working research question at all stages. This is your “anchor” when you get lost in the data. What are you addressing? What are you looking at and why? Your research question guides you through the thicket. It is common to have a whole host of questions about a phenomenon or case, both at the outset and throughout the study, but you should be able to pare it down to no more than two or three sentences when asked. These sentences should both clarify the intent of the research and explain why this is an important question to answer. More on refining your research question can be found in chapter 4.

Chances are, you will have already done some prior reading before coming up with your interest and your questions, but you may not have conducted a systematic literature review. This is the next crucial stage to be completed before venturing further. You don’t want to start collecting data and then realize that someone has already beaten you to the punch. A review of the literature that is already out there will let you know (1) if others have already done the study you are envisioning; (2) if others have done similar studies, which can help you out; and (3) what ideas or concepts are out there that can help you frame your study and make sense of your findings. More on literature reviews can be found in chapter 9.

In addition to reviewing the literature for similar studies to what you are proposing, it can be extremely helpful to find a study that inspires you. This may have absolutely nothing to do with the topic you are interested in but is written so beautifully or organized so interestingly or otherwise speaks to you in such a way that you want to post it somewhere to remind you of what you want to be doing. You might not understand this in the early stages—why would you find a study that has nothing to do with the one you are doing helpful? But trust me, when you are deep into analysis and writing, having an inspirational model in view can help you push through. If you are motivated to do something that might change the world, you probably have read something somewhere that inspired you. Go back to that original inspiration and read it carefully and see how they managed to convey the passion that you so appreciate.

At this stage, you are still just getting started. There are a lot of things to do before setting forth to collect data! You’ll want to consider and choose a research tradition and a set of data-collection techniques that both help you answer your research question and match all your aims and goals. For example, if you really want to help migrant workers speak for themselves, you might draw on feminist theory and participatory action research models. Chapters 3 and 4 will provide you with more information on epistemologies and approaches.

Next, you have to clarify your “units of analysis.” What is the level at which you are focusing your study? Often, the unit in qualitative research methods is individual people, or “human subjects.” But your units of analysis could just as well be organizations (colleges, hospitals) or programs or even whole nations. Think about what it is you want to be saying at the end of your study—are the insights you are hoping to make about people or about organizations or about something else entirely? A unit of analysis can even be a historical period! Every unit of analysis will call for a different kind of data collection and analysis and will produce different kinds of “findings” at the conclusion of your study. [2]

Regardless of what unit of analysis you select, you will probably have to consider the “human subjects” involved in your research. [3] Who are they? What interactions will you have with them—that is, what kind of data will you be collecting? Before answering these questions, define your population of interest and your research setting. Use your research question to help guide you.

Let’s use an example from a real study. In Geographies of Campus Inequality , Benson and Lee ( 2020 ) list three related research questions: “(1) What are the different ways that first-generation students organize their social, extracurricular, and academic activities at selective and highly selective colleges? (2) how do first-generation students sort themselves and get sorted into these different types of campus lives; and (3) how do these different patterns of campus engagement prepare first-generation students for their post-college lives?” (3).

Note that we are jumping into this a bit late, after Benson and Lee have described previous studies (the literature review) and what is known about first-generation college students and what is not known. They want to know about differences within this group, and they are interested in ones attending certain kinds of colleges because those colleges will be sites where academic and extracurricular pressures compete. That is the context for their three related research questions. What is the population of interest here? First-generation college students . What is the research setting? Selective and highly selective colleges . But a host of questions remain. Which students in the real world, which colleges? What about gender, race, and other identity markers? Will the students be asked questions? Are the students still in college, or will they be asked about what college was like for them? Will they be observed? Will they be shadowed? Will they be surveyed? Will they be asked to keep diaries of their time in college? How many students? How many colleges? For how long will they be observed?

Recommendation

Take a moment and write down suggestions for Benson and Lee before continuing on to what they actually did.

Have you written down your own suggestions? Good. Now let’s compare those with what they actually did. Benson and Lee drew on two sources of data: in-depth interviews with sixty-four first-generation students and survey data from a preexisting national survey of students at twenty-eight selective colleges. Let’s ignore the survey for our purposes here and focus on those interviews. The interviews were conducted between 2014 and 2016 at a single selective college, “Hilltop” (a pseudonym ). They employed a “purposive” sampling strategy to ensure an equal number of male-identifying and female-identifying students as well as equal numbers of White, Black, and Latinx students. Each student was interviewed once. Hilltop is a selective liberal arts college in the northeast that enrolls about three thousand students.

How did your suggestions match up to those actually used by the researchers in this study? It is possible your suggestions were too ambitious? Beginning qualitative researchers can often make that mistake. You want a research design that is both effective (it matches your question and goals) and doable. You will never be able to collect data from your entire population of interest (unless your research question is really so narrow to be relevant to very few people!), so you will need to come up with a good sample. Define the criteria for this sample, as Benson and Lee did when deciding to interview an equal number of students by gender and race categories. Define the criteria for your sample setting too. Hilltop is typical for selective colleges. That was a research choice made by Benson and Lee. For more on sampling and sampling choices, see chapter 5.

Benson and Lee chose to employ interviews. If you also would like to include interviews, you have to think about what will be asked in them. Most interview-based research involves an interview guide, a set of questions or question areas that will be asked of each participant. The research question helps you create a relevant interview guide. You want to ask questions whose answers will provide insight into your research question. Again, your research question is the anchor you will continually come back to as you plan for and conduct your study. It may be that once you begin interviewing, you find that people are telling you something totally unexpected, and this makes you rethink your research question. That is fine. Then you have a new anchor. But you always have an anchor. More on interviewing can be found in chapter 11.

Let’s imagine Benson and Lee also observed college students as they went about doing the things college students do, both in the classroom and in the clubs and social activities in which they participate. They would have needed a plan for this. Would they sit in on classes? Which ones and how many? Would they attend club meetings and sports events? Which ones and how many? Would they participate themselves? How would they record their observations? More on observation techniques can be found in both chapters 13 and 14.

At this point, the design is almost complete. You know why you are doing this study, you have a clear research question to guide you, you have identified your population of interest and research setting, and you have a reasonable sample of each. You also have put together a plan for data collection, which might include drafting an interview guide or making plans for observations. And so you know exactly what you will be doing for the next several months (or years!). To put the project into action, there are a few more things necessary before actually going into the field.

First, you will need to make sure you have any necessary supplies, including recording technology. These days, many researchers use their phones to record interviews. Second, you will need to draft a few documents for your participants. These include informed consent forms and recruiting materials, such as posters or email texts, that explain what this study is in clear language. Third, you will draft a research protocol to submit to your institutional review board (IRB) ; this research protocol will include the interview guide (if you are using one), the consent form template, and all examples of recruiting material. Depending on your institution and the details of your study design, it may take weeks or even, in some unfortunate cases, months before you secure IRB approval. Make sure you plan on this time in your project timeline. While you wait, you can continue to review the literature and possibly begin drafting a section on the literature review for your eventual presentation/publication. More on IRB procedures can be found in chapter 8 and more general ethical considerations in chapter 7.

Once you have approval, you can begin!

Research Design Checklist

Before data collection begins, do the following:

Write a paragraph explaining your aims and goals (personal/political, practical/strategic, professional/academic).
Define your research question; write two to three sentences that clarify the intent of the research and why this is an important question to answer.
Review the literature for similar studies that address your research question or similar research questions; think laterally about some literature that might be helpful or illuminating but is not exactly about the same topic.
Find a written study that inspires you—it may or may not be on the research question you have chosen.
Consider and choose a research tradition and set of data-collection techniques that (1) help answer your research question and (2) match your aims and goals.
Define your population of interest and your research setting.
Define the criteria for your sample (How many? Why these? How will you find them, gain access, and acquire consent?).
If you are conducting interviews, draft an interview guide.
If you are making observations, create a plan for observations (sites, times, recording, access).
Acquire any necessary technology (recording devices/software).
Draft consent forms that clearly identify the research focus and selection process.
Create recruiting materials (posters, email, texts).
Apply for IRB approval (proposal plus consent form plus recruiting materials).
Block out time for collecting data.
At the end of the chapter, you will find a " Research Design Checklist " that summarizes the main recommendations made here ↵
For example, if your focus is society and culture , you might collect data through observation or a case study. If your focus is individual lived experience , you are probably going to be interviewing some people. And if your focus is language and communication , you will probably be analyzing text (written or visual). ( Marshall and Rossman 2016:16 ). ↵
You may not have any "live" human subjects. There are qualitative research methods that do not require interactions with live human beings - see chapter 16 , "Archival and Historical Sources." But for the most part, you are probably reading this textbook because you are interested in doing research with people. The rest of the chapter will assume this is the case. ↵

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography.

A methodological tradition of inquiry and research design that focuses on an individual case (e.g., setting, institution, or sometimes an individual) in order to explore its complexity, history, and interactive parts. As an approach, it is particularly useful for obtaining a deep appreciation of an issue, event, or phenomenon of interest in its particular context.

The controlling force in research; can be understood as lying on a continuum from basic research (knowledge production) to action research (effecting change).

In its most basic sense, a theory is a story we tell about how the world works that can be tested with empirical evidence. In qualitative research, we use the term in a variety of ways, many of which are different from how they are used by quantitative researchers. Although some qualitative research can be described as “testing theory,” it is more common to “build theory” from the data using inductive reasoning , as done in Grounded Theory . There are so-called “grand theories” that seek to integrate a whole series of findings and stories into an overarching paradigm about how the world works, and much smaller theories or concepts about particular processes and relationships. Theory can even be used to explain particular methodological perspectives or approaches, as in Institutional Ethnography , which is both a way of doing research and a theory about how the world works.

Research that is interested in generating and testing hypotheses about how the world works.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction. This approach was pioneered by the sociologists Glaser and Strauss (1967). The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences. Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

Research that contributes knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment.

Research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems. There are two kinds: summative and formative .

Research in which an overall judgment about the effectiveness of a program or policy is made, often for the purpose of generalizing to other cases or programs. Generally uses qualitative research as a supplement to primary quantitative data analyses. Contrast formative evaluation research .

Research designed to improve a program or policy (to help “form” or shape its effectiveness); relies heavily on qualitative research methods. Contrast summative evaluation research

Research carried out at a particular organizational or community site with the intention of affecting change; often involves research subjects as participants of the study. See also participatory action research .

Research in which both researchers and participants work together to understand a problematic situation and change it for the better.

The level of the focus of analysis (e.g., individual people, organizations, programs, neighborhoods).

The large group of interest to the researcher. Although it will likely be impossible to design a study that incorporates or reaches all members of the population of interest, this should be clearly defined at the outset of a study so that a reasonable sample of the population can be taken. For example, if one is studying working-class college students, the sample may include twenty such students attending a particular college, while the population is “working-class college students.” In quantitative research, clearly defining the general population of interest is a necessary step in generalizing results from a sample. In qualitative research, defining the population is conceptually important for clarity.

A fictional name assigned to give anonymity to a person, group, or place. Pseudonyms are important ways of protecting the identity of research participants while still providing a “human element” in the presentation of qualitative data. There are ethical considerations to be made in selecting pseudonyms; some researchers allow research participants to choose their own.

A requirement for research involving human participants; the documentation of informed consent. In some cases, oral consent or assent may be sufficient, but the default standard is a single-page easy-to-understand form that both the researcher and the participant sign and date. Under federal guidelines, all researchers "shall seek such consent only under circumstances that provide the prospective subject or the representative sufficient opportunity to consider whether or not to participate and that minimize the possibility of coercion or undue influence. The information that is given to the subject or the representative shall be in language understandable to the subject or the representative. No informed consent, whether oral or written, may include any exculpatory language through which the subject or the representative is made to waive or appear to waive any of the subject's rights or releases or appears to release the investigator, the sponsor, the institution, or its agents from liability for negligence" (21 CFR 50.20). Your IRB office will be able to provide a template for use in your study .

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

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Methodology
Descriptive Research Design | Definition, Methods & Examples

Descriptive Research Design | Definition, Methods & Examples

Published on 5 May 2022 by Shona McCombes . Revised on 10 October 2022.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when , and how questions , but not why questions.

A descriptive research design can use a wide variety of research methods to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

When to use a descriptive research design, descriptive research methods.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when, and where it happens.

How has the London housing market changed over the past 20 years?
Do customers of company X prefer product Y or product Z?
What are the main genetic, behavioural, and morphological differences between European wildcats and domestic cats?
What are the most popular online news sources among under-18s?
How prevalent is disease A in population B?

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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analysed for frequencies, averages, and patterns. Common uses of surveys include:

Describing the demographics of a country or region
Gauging public opinion on political and social topics
Evaluating satisfaction with a company’s products or an organisation’s services

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social, and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models, or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event, or organisation). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalisable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

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Dissertation Structure & Layout 101: How to structure your dissertation, thesis or research project.

By: Derek Jansen (MBA) Reviewed By: David Phair (PhD) | July 2019

So, you’ve got a decent understanding of what a dissertation is , you’ve chosen your topic and hopefully you’ve received approval for your research proposal . Awesome! Now its time to start the actual dissertation or thesis writing journey.

To craft a high-quality document, the very first thing you need to understand is dissertation structure . In this post, we’ll walk you through the generic dissertation structure and layout, step by step. We’ll start with the big picture, and then zoom into each chapter to briefly discuss the core contents. If you’re just starting out on your research journey, you should start with this post, which covers the big-picture process of how to write a dissertation or thesis .

Dissertation structure and layout - the basics

The Caveat

In this post, we’ll be discussing a traditional dissertation/thesis structure and layout, which is generally used for social science research across universities, whether in the US, UK, Europe or Australia. However, some universities may have small variations on this structure (extra chapters, merged chapters, slightly different ordering, etc).

So, always check with your university if they have a prescribed structure or layout that they expect you to work with. If not, it’s safe to assume the structure we’ll discuss here is suitable. And even if they do have a prescribed structure, you’ll still get value from this post as we’ll explain the core contents of each section.

Overview: S tructuring a dissertation or thesis

Acknowledgements page
Abstract (or executive summary)
Table of contents , list of figures and tables
Chapter 1: Introduction
Chapter 2: Literature review
Chapter 3: Methodology
Chapter 4: Results
Chapter 5: Discussion
Chapter 6: Conclusion
Reference list

As I mentioned, some universities will have slight variations on this structure. For example, they want an additional “personal reflection chapter”, or they might prefer the results and discussion chapter to be merged into one. Regardless, the overarching flow will always be the same, as this flow reflects the research process , which we discussed here – i.e.:

The introduction chapter presents the core research question and aims .
The literature review chapter assesses what the current research says about this question.
The methodology, results and discussion chapters go about undertaking new research about this question.
The conclusion chapter (attempts to) answer the core research question .

In other words, the dissertation structure and layout reflect the research process of asking a well-defined question(s), investigating, and then answering the question – see below.

A dissertation's structure reflect the research process

To restate that – the structure and layout of a dissertation reflect the flow of the overall research process . This is essential to understand, as each chapter will make a lot more sense if you “get” this concept. If you’re not familiar with the research process, read this post before going further.

Right. Now that we’ve covered the big picture, let’s dive a little deeper into the details of each section and chapter. Oh and by the way, you can also grab our free dissertation/thesis template here to help speed things up.

The title page of your dissertation is the very first impression the marker will get of your work, so it pays to invest some time thinking about your title. But what makes for a good title? A strong title needs to be 3 things:

Succinct (not overly lengthy or verbose)
Specific (not vague or ambiguous)
Representative of the research you’re undertaking (clearly linked to your research questions)

Typically, a good title includes mention of the following:

The broader area of the research (i.e. the overarching topic)
The specific focus of your research (i.e. your specific context)
Indication of research design (e.g. quantitative , qualitative , or mixed methods ).

For example:

A quantitative investigation [research design] into the antecedents of organisational trust [broader area] in the UK retail forex trading market [specific context/area of focus].

Again, some universities may have specific requirements regarding the format and structure of the title, so it’s worth double-checking expectations with your institution (if there’s no mention in the brief or study material).

Acknowledgements

This page provides you with an opportunity to say thank you to those who helped you along your research journey. Generally, it’s optional (and won’t count towards your marks), but it is academic best practice to include this.

So, who do you say thanks to? Well, there’s no prescribed requirements, but it’s common to mention the following people:

Your dissertation supervisor or committee.
Any professors, lecturers or academics that helped you understand the topic or methodologies.
Any tutors, mentors or advisors.
Your family and friends, especially spouse (for adult learners studying part-time).

There’s no need for lengthy rambling. Just state who you’re thankful to and for what (e.g. thank you to my supervisor, John Doe, for his endless patience and attentiveness) – be sincere. In terms of length, you should keep this to a page or less.

Abstract or executive summary

The dissertation abstract (or executive summary for some degrees) serves to provide the first-time reader (and marker or moderator) with a big-picture view of your research project. It should give them an understanding of the key insights and findings from the research, without them needing to read the rest of the report – in other words, it should be able to stand alone .

For it to stand alone, your abstract should cover the following key points (at a minimum):

Your research questions and aims – what key question(s) did your research aim to answer?
Your methodology – how did you go about investigating the topic and finding answers to your research question(s)?
Your findings – following your own research, what did do you discover?
Your conclusions – based on your findings, what conclusions did you draw? What answers did you find to your research question(s)?

So, in much the same way the dissertation structure mimics the research process, your abstract or executive summary should reflect the research process, from the initial stage of asking the original question to the final stage of answering that question.

In practical terms, it’s a good idea to write this section up last , once all your core chapters are complete. Otherwise, you’ll end up writing and rewriting this section multiple times (just wasting time). For a step by step guide on how to write a strong executive summary, check out this post .

Need a helping hand?

This section is straightforward. You’ll typically present your table of contents (TOC) first, followed by the two lists – figures and tables. I recommend that you use Microsoft Word’s automatic table of contents generator to generate your TOC. If you’re not familiar with this functionality, the video below explains it simply:

If you find that your table of contents is overly lengthy, consider removing one level of depth. Oftentimes, this can be done without detracting from the usefulness of the TOC.

Right, now that the “admin” sections are out of the way, its time to move on to your core chapters. These chapters are the heart of your dissertation and are where you’ll earn the marks. The first chapter is the introduction chapter – as you would expect, this is the time to introduce your research…

It’s important to understand that even though you’ve provided an overview of your research in your abstract, your introduction needs to be written as if the reader has not read that (remember, the abstract is essentially a standalone document). So, your introduction chapter needs to start from the very beginning, and should address the following questions:

What will you be investigating (in plain-language, big picture-level)?
Why is that worth investigating? How is it important to academia or business? How is it sufficiently original?
What are your research aims and research question(s)? Note that the research questions can sometimes be presented at the end of the literature review (next chapter).
What is the scope of your study? In other words, what will and won’t you cover ?
How will you approach your research? In other words, what methodology will you adopt?
How will you structure your dissertation? What are the core chapters and what will you do in each of them?

These are just the bare basic requirements for your intro chapter. Some universities will want additional bells and whistles in the intro chapter, so be sure to carefully read your brief or consult your research supervisor.

If done right, your introduction chapter will set a clear direction for the rest of your dissertation. Specifically, it will make it clear to the reader (and marker) exactly what you’ll be investigating, why that’s important, and how you’ll be going about the investigation. Conversely, if your introduction chapter leaves a first-time reader wondering what exactly you’ll be researching, you’ve still got some work to do.

Now that you’ve set a clear direction with your introduction chapter, the next step is the literature review . In this section, you will analyse the existing research (typically academic journal articles and high-quality industry publications), with a view to understanding the following questions:

What does the literature currently say about the topic you’re investigating?
Is the literature lacking or well established? Is it divided or in disagreement?
How does your research fit into the bigger picture?
How does your research contribute something original?
How does the methodology of previous studies help you develop your own?

Depending on the nature of your study, you may also present a conceptual framework towards the end of your literature review, which you will then test in your actual research.

Again, some universities will want you to focus on some of these areas more than others, some will have additional or fewer requirements, and so on. Therefore, as always, its important to review your brief and/or discuss with your supervisor, so that you know exactly what’s expected of your literature review chapter.

Now that you’ve investigated the current state of knowledge in your literature review chapter and are familiar with the existing key theories, models and frameworks, its time to design your own research. Enter the methodology chapter – the most “science-ey” of the chapters…

In this chapter, you need to address two critical questions:

Exactly HOW will you carry out your research (i.e. what is your intended research design)?
Exactly WHY have you chosen to do things this way (i.e. how do you justify your design)?

Remember, the dissertation part of your degree is first and foremost about developing and demonstrating research skills . Therefore, the markers want to see that you know which methods to use, can clearly articulate why you’ve chosen then, and know how to deploy them effectively.

Importantly, this chapter requires detail – don’t hold back on the specifics. State exactly what you’ll be doing, with who, when, for how long, etc. Moreover, for every design choice you make, make sure you justify it.

In practice, you will likely end up coming back to this chapter once you’ve undertaken all your data collection and analysis, and revise it based on changes you made during the analysis phase. This is perfectly fine. Its natural for you to add an additional analysis technique, scrap an old one, etc based on where your data lead you. Of course, I’m talking about small changes here – not a fundamental switch from qualitative to quantitative, which will likely send your supervisor in a spin!

You’ve now collected your data and undertaken your analysis, whether qualitative, quantitative or mixed methods. In this chapter, you’ll present the raw results of your analysis . For example, in the case of a quant study, you’ll present the demographic data, descriptive statistics, inferential statistics , etc.

Typically, Chapter 4 is simply a presentation and description of the data, not a discussion of the meaning of the data. In other words, it’s descriptive, rather than analytical – the meaning is discussed in Chapter 5. However, some universities will want you to combine chapters 4 and 5, so that you both present and interpret the meaning of the data at the same time. Check with your institution what their preference is.

Now that you’ve presented the data analysis results, its time to interpret and analyse them. In other words, its time to discuss what they mean, especially in relation to your research question(s).

What you discuss here will depend largely on your chosen methodology. For example, if you’ve gone the quantitative route, you might discuss the relationships between variables . If you’ve gone the qualitative route, you might discuss key themes and the meanings thereof. It all depends on what your research design choices were.

Most importantly, you need to discuss your results in relation to your research questions and aims, as well as the existing literature. What do the results tell you about your research questions? Are they aligned with the existing research or at odds? If so, why might this be? Dig deep into your findings and explain what the findings suggest, in plain English.

The final chapter – you’ve made it! Now that you’ve discussed your interpretation of the results, its time to bring it back to the beginning with the conclusion chapter . In other words, its time to (attempt to) answer your original research question s (from way back in chapter 1). Clearly state what your conclusions are in terms of your research questions. This might feel a bit repetitive, as you would have touched on this in the previous chapter, but its important to bring the discussion full circle and explicitly state your answer(s) to the research question(s).

Next, you’ll typically discuss the implications of your findings? In other words, you’ve answered your research questions – but what does this mean for the real world (or even for academia)? What should now be done differently, given the new insight you’ve generated?

Lastly, you should discuss the limitations of your research, as well as what this means for future research in the area. No study is perfect, especially not a Masters-level. Discuss the shortcomings of your research. Perhaps your methodology was limited, perhaps your sample size was small or not representative, etc, etc. Don’t be afraid to critique your work – the markers want to see that you can identify the limitations of your work. This is a strength, not a weakness. Be brutal!

This marks the end of your core chapters – woohoo! From here on out, it’s pretty smooth sailing.

The reference list is straightforward. It should contain a list of all resources cited in your dissertation, in the required format, e.g. APA , Harvard, etc.

It’s essential that you use reference management software for your dissertation. Do NOT try handle your referencing manually – its far too error prone. On a reference list of multiple pages, you’re going to make mistake. To this end, I suggest considering either Mendeley or Zotero. Both are free and provide a very straightforward interface to ensure that your referencing is 100% on point. I’ve included a simple how-to video for the Mendeley software (my personal favourite) below:

Some universities may ask you to include a bibliography, as opposed to a reference list. These two things are not the same . A bibliography is similar to a reference list, except that it also includes resources which informed your thinking but were not directly cited in your dissertation. So, double-check your brief and make sure you use the right one.

The very last piece of the puzzle is the appendix or set of appendices. This is where you’ll include any supporting data and evidence. Importantly, supporting is the keyword here.

Your appendices should provide additional “nice to know”, depth-adding information, which is not critical to the core analysis. Appendices should not be used as a way to cut down word count (see this post which covers how to reduce word count ). In other words, don’t place content that is critical to the core analysis here, just to save word count. You will not earn marks on any content in the appendices, so don’t try to play the system!

Time to recap…

And there you have it – the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows:

Acknowledgments page

Most importantly, the core chapters should reflect the research process (asking, investigating and answering your research question). Moreover, the research question(s) should form the golden thread throughout your dissertation structure. Everything should revolve around the research questions, and as you’ve seen, they should form both the start point (i.e. introduction chapter) and the endpoint (i.e. conclusion chapter).

I hope this post has provided you with clarity about the traditional dissertation/thesis structure and layout. If you have any questions or comments, please leave a comment below, or feel free to get in touch with us. Also, be sure to check out the rest of the Grad Coach Blog .

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project.

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36 Comments

many thanks i found it very useful

Glad to hear that, Arun. Good luck writing your dissertation.

Such clear practical logical advice. I very much needed to read this to keep me focused in stead of fretting.. Perfect now ready to start my research!

what about scientific fields like computer or engineering thesis what is the difference in the structure? thank you very much

Thanks so much this helped me a lot!

Very helpful and accessible. What I like most is how practical the advice is along with helpful tools/ links.

Thanks Ade!

Thank you so much sir.. It was really helpful..

You’re welcome!

Hi! How many words maximum should contain the abstract?

Thank you so much 😊 Find this at the right moment

You’re most welcome. Good luck with your dissertation.

best ever benefit i got on right time thank you

Many times Clarity and vision of destination of dissertation is what makes the difference between good ,average and great researchers the same way a great automobile driver is fast with clarity of address and Clear weather conditions .

I guess Great researcher = great ideas + knowledge + great and fast data collection and modeling + great writing + high clarity on all these

You have given immense clarity from start to end.

Morning. Where will I write the definitions of what I’m referring to in my report?

Thank you so much Derek, I was almost lost! Thanks a tonnnn! Have a great day!

Thanks ! so concise and valuable

This was very helpful. Clear and concise. I know exactly what to do now.

Thank you for allowing me to go through briefly. I hope to find time to continue.

Really useful to me. Thanks a thousand times

Very interesting! It will definitely set me and many more for success. highly recommended.

Thank you soo much sir, for the opportunity to express my skills

Usefull, thanks a lot. Really clear

Very nice and easy to understand. Thank you .

That was incredibly useful. Thanks Grad Coach Crew!

My stress level just dropped at least 15 points after watching this. Just starting my thesis for my grad program and I feel a lot more capable now! Thanks for such a clear and helpful video, Emma and the GradCoach team!

Do we need to mention the number of words the dissertation contains in the main document?

It depends on your university’s requirements, so it would be best to check with them 🙂

Such a helpful post to help me get started with structuring my masters dissertation, thank you!

Great video; I appreciate that helpful information

It is so necessary or avital course

This blog is very informative for my research. Thank you

Doctoral students are required to fill out the National Research Council’s Survey of Earned Doctorates

wow this is an amazing gain in my life

This is so good

How can i arrange my specific objectives in my dissertation?

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Research Methods Guide: Research Design & Method

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FAQ: Research Design & Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question. A research method is a strategy used to implement that plan. Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal. It depends on what subjects (and who) you want to study. Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus. To answer these questions, you need to make a decision about how to collect your data. Most frequently used methods include:

Observation / Participant Observation
Focus Groups
Experiments
Secondary Data Analysis / Archival Study
Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity. For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider. An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time. Using a survey helps you collect more data quickly, yet it may lack details. So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

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Starting the research process

A Beginner's Guide to Starting the Research Process

When you have to write a thesis or dissertation , it can be hard to know where to begin, but there are some clear steps you can follow.

The research process often begins with a very broad idea for a topic you’d like to know more about. You do some preliminary research to identify a problem . After refining your research questions , you can lay out the foundations of your research design , leading to a proposal that outlines your ideas and plans.

This article takes you through the first steps of the research process, helping you narrow down your ideas and build up a strong foundation for your research project.

Step 1: choose your topic, step 2: identify a problem, step 3: formulate research questions, step 4: create a research design, step 5: write a research proposal, other interesting articles.

First you have to come up with some ideas. Your thesis or dissertation topic can start out very broad. Think about the general area or field you’re interested in—maybe you already have specific research interests based on classes you’ve taken, or maybe you had to consider your topic when applying to graduate school and writing a statement of purpose .

Even if you already have a good sense of your topic, you’ll need to read widely to build background knowledge and begin narrowing down your ideas. Conduct an initial literature review to begin gathering relevant sources. As you read, take notes and try to identify problems, questions, debates, contradictions and gaps. Your aim is to narrow down from a broad area of interest to a specific niche.

Make sure to consider the practicalities: the requirements of your programme, the amount of time you have to complete the research, and how difficult it will be to access sources and data on the topic. Before moving onto the next stage, it’s a good idea to discuss the topic with your thesis supervisor.

>>Read more about narrowing down a research topic

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So you’ve settled on a topic and found a niche—but what exactly will your research investigate, and why does it matter? To give your project focus and purpose, you have to define a research problem .

The problem might be a practical issue—for example, a process or practice that isn’t working well, an area of concern in an organization’s performance, or a difficulty faced by a specific group of people in society.

Alternatively, you might choose to investigate a theoretical problem—for example, an underexplored phenomenon or relationship, a contradiction between different models or theories, or an unresolved debate among scholars.

To put the problem in context and set your objectives, you can write a problem statement . This describes who the problem affects, why research is needed, and how your research project will contribute to solving it.

>>Read more about defining a research problem

Next, based on the problem statement, you need to write one or more research questions . These target exactly what you want to find out. They might focus on describing, comparing, evaluating, or explaining the research problem.

A strong research question should be specific enough that you can answer it thoroughly using appropriate qualitative or quantitative research methods. It should also be complex enough to require in-depth investigation, analysis, and argument. Questions that can be answered with “yes/no” or with easily available facts are not complex enough for a thesis or dissertation.

In some types of research, at this stage you might also have to develop a conceptual framework and testable hypotheses .

>>See research question examples

The research design is a practical framework for answering your research questions. It involves making decisions about the type of data you need, the methods you’ll use to collect and analyze it, and the location and timescale of your research.

There are often many possible paths you can take to answering your questions. The decisions you make will partly be based on your priorities. For example, do you want to determine causes and effects, draw generalizable conclusions, or understand the details of a specific context?

You need to decide whether you will use primary or secondary data and qualitative or quantitative methods . You also need to determine the specific tools, procedures, and materials you’ll use to collect and analyze your data, as well as your criteria for selecting participants or sources.

>>Read more about creating a research design

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Finally, after completing these steps, you are ready to complete a research proposal . The proposal outlines the context, relevance, purpose, and plan of your research.

As well as outlining the background, problem statement, and research questions, the proposal should also include a literature review that shows how your project will fit into existing work on the topic. The research design section describes your approach and explains exactly what you will do.

You might have to get the proposal approved by your supervisor before you get started, and it will guide the process of writing your thesis or dissertation.

>>Read more about writing a research proposal

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.

Methodology

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

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Architecture student in Northern Virginia embraces deaf community in design and in life

Craig Newcomb

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Washington-Alexandria Architecture Center (WAAC) graduate student Kim Le’s master’s thesis is on deaf architecture. Going beyond conventional research, she is both learning American Sign Language and is active in the greater Washington, D.C., metro area deaf community. “I think my thesis in a way has changed my life. By being fully immersed in the deaf community, I just have a completely different perspective now,” said Le.

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Research Design – Types, Methods and Examples

Research Design

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Descriptive Research Design

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Experimental Research Design

Quasi-experimental Research Design

Case Study Research Design

Longitudinal Research Design

Structure of Research Design

Example of Research Design

How to Write Research Design

When to Write Research Design

Purpose of Research Design

Applications of Research Design

Advantages of Research Design

Research Design Vs Research Methodology

Muhammad Hassan

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How to Write a Research Design – Guide with Examples

Step 1: Establish Priorities for Research Design

Step 2: Data Type you Need for Research

Primary Data Vs. Secondary Data

Need help with a thesis chapter?

Step 3: Data Collection Techniques

Step 4: Procedure of Data Analysis

Quantitative Data Analysis

Qualitative Data Analysis

Step 5: Write your Research Proposal

How to Write a Research Design – Conclusion

Frequently Asked Questions

How to write a research design?

How to write the design section of a research paper?

How to write a research design in methodology?

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Research Design: What it is, Elements & Types

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