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How to read and understand a scientific paper

How to read and understand a scientific paper: a guide for non-scientists, london school of economics and political science, jennifer raff.

From vaccinations to climate change, getting science wrong has very real consequences. But journal articles, a primary way science is communicated in academia, are a different format to newspaper articles or blogs and require a level of skill and undoubtedly a greater amount of patience. Here  Jennifer Raff   has prepared a helpful guide for non-scientists on how to read a scientific paper. These steps and tips will be useful to anyone interested in the presentation of scientific findings and raise important points for scientists to consider with their own writing practice.

My post,  The truth about vaccinations: Your physician knows more than the University of Google  sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that  their  paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection, outbreaks happen.

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field. And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a  basic  understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a  primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a  review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice

Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g.  the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven.  Tip:  g oogle  “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by  Pubmed . [EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out  Web of Science  for a more complete index of science journals. And please feel free to share other resources in the comments!]  Beware of  questionable journals .

As you read, write down  every single word  that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the only part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract last. I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain why this research has been done in order to understand it.

4.   Identify the SPECIFIC QUESTION(S)

What  exactly  are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read this one  and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean  literally  draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

Image credit: author

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7.   Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results  mean , just write down what they  are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but  here , and here   are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

Things to pay attention to in the results section:

• Any time the words “significant” or “non-significant” are used. These have precise statistical meanings. Read more about this  here .
• If there are graphs, do they have  error bars  on them? For certain types of studies, a lack of confidence intervals is a major red flag.
• The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors think the results mean? Do you agree with them? Can you come up with any alternative way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP:  (Don’t neglect doing this)  What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

UPDATE: If you would like to see an example of how to read a science paper using this framework, you can find one  here .

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

I’ve written a shorter version of this guide for teachers to hand out to their classes. If you’d like a PDF, shoot me an email: jenniferraff (at) utexas (dot) edu. For further comments and additional questions on this guide, please see the Comments Section on  the original post .

This piece originally appeared on the  author’s personal blog  and is reposted with permission.

Featured image credit:  Scientists in a laboratory of the University of La Rioja  by  Urcomunicacion  (Wikimedia CC BY3.0)

Note: This article gives the views of the authors, and not the position of the LSE Impact blog, nor of the London School of Economics. Please review our  Comments Policy  if you have any concerns on posting a comment below.

Jennifer Raff (Indiana University—dual Ph.D. in genetics and bioanthropology) is an assistant professor in the Department of Anthropology, University of Kansas, director and Principal Investigator of the KU Laboratory of Human Population Genomics, and assistant director of KU’s Laboratory of Biological Anthropology. She is also a research affiliate with the University of Texas anthropological genetics laboratory. She is keenly interested in public outreach and scientific literacy, writing about topics in science and pseudoscience for her blog ( violentmetaphors.com ), the Huffington Post, and for the  Social Evolution Forum .

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Organizing Your Social Sciences Research Paper

• Reading Research Effectively
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• 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
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• Bibliography

Reading a Scholarly Article or Research Paper

Identifying a research problem to investigate usually requires a preliminary search for and critical review of the literature in order to gain an understanding about how scholars have examined a topic. Scholars rarely structure research studies in a way that can be followed like a story; they are complex and detail-intensive and often written in a descriptive and conclusive narrative form. However, in the social and behavioral sciences, journal articles and stand-alone research reports are generally organized in a consistent format that makes it easier to compare and contrast studies and to interpret their contents.

General Reading Strategies

W hen you first read an article or research paper, focus on asking specific questions about each section. This strategy can help with overall comprehension and with understanding how the content relates [or does not relate] to the problem you want to investigate. As you review more and more studies, the process of understanding and critically evaluating the research will become easier because the content of what you review will begin to coalescence around common themes and patterns of analysis. Below are recommendations on how to read each section of a research paper effectively. Note that the sections to read are out of order from how you will find them organized in a journal article or research paper.

1.  Abstract

The abstract summarizes the background, methods, results, discussion, and conclusions of a scholarly article or research paper. Use the abstract to filter out sources that may have appeared useful when you began searching for information but, in reality, are not relevant. Questions to consider when reading the abstract are:

• Is this study related to my question or area of research?
• What is this study about and why is it being done ?
• What is the working hypothesis or underlying thesis?
• What is the primary finding of the study?
• Are there words or terminology that I can use to either narrow or broaden the parameters of my search for more information?

2.  Introduction

If, after reading the abstract, you believe the paper may be useful, focus on examining the research problem and identifying the questions the author is trying to address. This information is usually located within the first few paragraphs of the introduction or in the concluding paragraph. Look for information about how and in what way this relates to what you are investigating. In addition to the research problem, the introduction should provide the main argument and theoretical framework of the study and, in the last paragraphs of the introduction, describe what the author(s) intend to accomplish. Questions to consider when reading the introduction include:

• What is this study trying to prove or disprove?
• What is the author(s) trying to test or demonstrate?
• What do we already know about this topic and what gaps does this study try to fill or contribute a new understanding to the research problem?
• Why should I care about what is being investigated?
• Will this study tell me anything new related to the research problem I am investigating?

3.  Literature Review

The literature review describes and critically evaluates what is already known about a topic. Read the literature review to obtain a big picture perspective about how the topic has been studied and to begin the process of seeing where your potential study fits within the domain of prior research. Questions to consider when reading the literature review include:

• W hat other research has been conducted about this topic and what are the main themes that have emerged?
• What does prior research reveal about what is already known about the topic and what remains to be discovered?
• What have been the most important past findings about the research problem?
• How has prior research led the author(s) to conduct this particular study?
• Is there any prior research that is unique or groundbreaking?
• Are there any studies I could use as a model for designing and organizing my own study?

4.  Discussion/Conclusion

The discussion and conclusion are usually the last two sections of text in a scholarly article or research report. They reveal how the author(s) interpreted the findings of their research and presented recommendations or courses of action based on those findings. Often in the conclusion, the author(s) highlight recommendations for further research that can be used to develop your own study. Questions to consider when reading the discussion and conclusion sections include:

• What is the overall meaning of the study and why is this important? [i.e., how have the author(s) addressed the " So What? " question].
• What do you find to be the most important ways that the findings have been interpreted?
• What are the weaknesses in their argument?
• Do you believe conclusions about the significance of the study and its findings are valid?
• What limitations of the study do the author(s) describe and how might this help formulate my own research?
• Does the conclusion contain any recommendations for future research?

5.  Methods/Methodology

The methods section describes the materials, techniques, and procedures for gathering information used to examine the research problem. If what you have read so far closely supports your understanding of the topic, then move on to examining how the author(s) gathered information during the research process. Questions to consider when reading the methods section include:

• Did the study use qualitative [based on interviews, observations, content analysis], quantitative [based on statistical analysis], or a mixed-methods approach to examining the research problem?
• What was the type of information or data used?
• Could this method of analysis be repeated and can I adopt the same approach?
• Is enough information available to repeat the study or should new data be found to expand or improve understanding of the research problem?

6.  Results

After reading the above sections, you should have a clear understanding of the general findings of the study. Therefore, read the results section to identify how key findings were discussed in relation to the research problem. If any non-textual elements [e.g., graphs, charts, tables, etc.] are confusing, focus on the explanations about them in the text. Questions to consider when reading the results section include:

• W hat did the author(s) find and how did they find it?
• Does the author(s) highlight any findings as most significant?
• Are the results presented in a factual and unbiased way?
• Does the analysis of results in the discussion section agree with how the results are presented?
• Is all the data present and did the author(s) adequately address gaps?
• What conclusions do you formulate from this data and does it match with the author's conclusions?

7.  References

The references list the sources used by the author(s) to document what prior research and information was used when conducting the study. After reviewing the article or research paper, use the references to identify additional sources of information on the topic and to examine critically how these sources supported the overall research agenda. Questions to consider when reading the references include:

• Do the sources cited by the author(s) reflect a diversity of disciplinary viewpoints, i.e., are the sources all from a particular field of study or do the sources reflect multiple areas of study?
• Are there any unique or interesting sources that could be incorporated into my study?
• What other authors are respected in this field, i.e., who has multiple works cited or is cited most often by others?
• What other research should I review to clarify any remaining issues or that I need more information about?

NOTE :  A final strategy in reviewing research is to copy and paste the title of the source [journal article, book, research report] into Google Scholar . If it appears, look for a "cited by" followed by a hyperlinked number [e.g., Cited by 45]. This number indicates how many times the study has been subsequently cited in other, more recently published works. This strategy, known as citation tracking, can be an effective means of expanding your review of pertinent literature based on a study you have found useful and how scholars have cited it. The same strategies described above can be applied to reading articles you find in the list of cited by references.

Reading Tip

Specific Reading Strategies

Effectively reading scholarly research is an acquired skill that involves attention to detail and an ability to comprehend complex ideas, data, and theoretical concepts in a way that applies logically to the research problem you are investigating. Here are some specific reading strategies to consider.

As You are Reading

• Focus on information that is most relevant to the research problem; skim over the other parts.
• As noted above, read content out of order! This isn't a novel; you want to start with the spoiler to quickly assess the relevance of the study.
• Think critically about what you read and seek to build your own arguments; not everything may be entirely valid, examined effectively, or thoroughly investigated.
• Look up the definitions of unfamiliar words, concepts, or terminology. A good scholarly source is Credo Reference .

Taking notes as you read will save time when you go back to examine your sources. Here are some suggestions:

• Mark or highlight important text as you read [e.g., you can use the highlight text  feature in a PDF document]
• Take notes in the margins [e.g., Adobe Reader offers pop-up sticky notes].
• Highlight important quotations; consider using different colors to differentiate between quotes and other types of important text.
• Summarize key points about the study at the end of the paper. To save time, these can be in the form of a concise bulleted list of statements [e.g., intro has provides historical background; lit review has important sources; good conclusions].

Write down thoughts that come to mind that may help clarify your understanding of the research problem. Here are some examples of questions to ask yourself:

• Do I understand all of the terminology and key concepts?
• Do I understand the parts of this study most relevant to my topic?
• What specific problem does the research address and why is it important?
• Are there any issues or perspectives the author(s) did not consider?
• Do I have any reason to question the validity or reliability of this research?
• How do the findings relate to my research interests and to other works which I have read?

Adapted from text originally created by Holly Burt, Behavioral Sciences Librarian, USC Libraries, April 2018.

Another Reading Tip

When is it Important to Read the Entire Article or Research Paper

Laubepin argues, "Very few articles in a field are so important that every word needs to be read carefully." However, this implies that some studies are worth reading carefully. As painful and time-consuming as it may seem, there are valid reasons for reading a study in its entirety from beginning to end. Here are some examples:

• Studies Published Very Recently .  The author(s) of a recent, well written study will provide a survey of the most important or impactful prior research in the literature review section. This can establish an understanding of how scholars in the past addressed the research problem. In addition, the most recently published sources will highlight what is currently known and what gaps in understanding currently exist about a topic, usually in the form of the need for further research in the conclusion .
• Surveys of the Research Problem .  Some papers provide a comprehensive analytical overview of the research problem. Reading this type of study can help you understand underlying issues and discover why scholars have chosen to investigate the topic. This is particularly important if the study was published very recently because the author(s) should cite all or most of the key prior research on the topic. Note that, if it is a long-standing problem, there may be studies that specifically review the literature to identify gaps that remain. These studies often include the word review in their title [e.g., Hügel, Stephan, and Anna R. Davies. "Public Participation, Engagement, and Climate Change Adaptation: A Review of the Research Literature." Wiley Interdisciplinary Reviews: Climate Change 11 (July-August 2020): https://doi.org/10.1002/ wcc.645].
• Highly Cited .  If you keep coming across the same citation to a study while you are reviewing the literature, this implies it was foundational in establishing an understanding of the research problem or the study had a significant impact within the literature [positive or negative]. Carefully reading a highly cited source can help you understand how the topic emerged and motivated scholars to further investigate the problem. It also could be a study you need to cite as foundational in your own paper to demonstrate to the reader that you understand the roots of the problem.
• Historical Overview .  Knowing the historical background of a research problem may not be the focus of your analysis. Nevertheless, carefully reading a study that provides a thorough description and analysis of the history behind an event, issue, or phenomenon can add important context to understanding the topic and what aspect of the problem you may want to examine further.
• Innovative Methodological Design .  Some studies are significant and worth reading in their entirety because the author(s) designed a unique or innovative approach to researching the problem. This may justify reading the entire study because it can motivate you to think creatively about pursuing an alternative or non-traditional approach to examining your topic of interest. These types of studies are generally easy to identify because they are often cited in others works because of their unique approach to studying the research problem.
• Cross-disciplinary Approach .  R eviewing studies produced outside of your discipline is an essential component of investigating research problems in the social and behavioral sciences. Consider reading a study that was conducted by author(s) based in a different discipline [e.g., an anthropologist studying political cultures; a study of hiring practices in companies published in a sociology journal]. This approach can generate a new understanding or a unique perspective about the topic . If you are not sure how to search for studies published in a discipline outside of your major or of the course you are taking, contact a librarian for assistance.

Laubepin, Frederique. How to Read (and Understand) a Social Science Journal Article . Inter-University Consortium for Political and Social Research (ISPSR), 2013; Shon, Phillip Chong Ho. How to Read Journal Articles in the Social Sciences: A Very Practical Guide for Students . 2nd edition. Thousand Oaks, CA: Sage, 2015; Lockhart, Tara, and Mary Soliday. "The Critical Place of Reading in Writing Transfer (and Beyond): A Report of Student Experiences." Pedagogy 16 (2016): 23-37; Maguire, Moira, Ann Everitt Reynolds, and Brid Delahunt. "Reading to Be: The Role of Academic Reading in Emergent Academic and Professional Student Identities." Journal of University Teaching and Learning Practice 17 (2020): 5-12.

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How to read a scientific paper: a step-by-step guide

Scientific paper format

How to read a scientific paper in 3 steps, step 1: identify your motivations for reading a scientific paper, step 2: use selective reading to gain a high-level understanding of the scientific paper, step 3: read straight through to achieve a deep understanding of a scientific paper, frequently asked questions about reading a scientific paper efficiently, related articles.

A scientific paper is a complex document. Scientific papers are divided into multiple sections and frequently contain jargon and long sentences that make reading difficult. The process of reading a scientific paper to obtain information can often feel overwhelming for an early career researcher.

But the good news is that you can acquire the skill of efficiently reading a scientific paper, and you can learn how to painlessly obtain the information you need.

In this guide, we show you how to read a scientific paper step-by-step. You will learn:

• The scientific paper format
• How to identify your reasons for reading a scientific paper
• How to skim a paper
• How to achieve a deep understanding of a paper.

Using these steps for reading a scientific paper will help you:

• Obtain information efficiently
• Retain knowledge more effectively
• Allocate sufficient time to your reading task.

The steps below are the result of research into how scientists read scientific papers and our own experiences as scientists.

Firstly, how is a scientific paper structured?

The main sections are Abstract, Introduction, Methods, Results, and Discussion. In the table below, we describe the purpose of each component of a scientific paper.

Because the structured format of a scientific paper makes it easy to find the information you need, a common technique for reading a scientific paper is to cherry-pick sections and jump around the paper.

In a YouTube video, Dr. Amina Yonis shows this nonlinear practice for reading a scientific paper. She justifies her technique by stating that “By reading research papers like this, you are enabling yourself to have a disciplined approach, and it prevents yourself from drowning in the details before you even get a bird’s-eye view”.

Selective reading is a skill that can help you read faster and engage with the material presented. In his article on active vs. passive reading of scientific papers, cell biologist Tung-Tien Sun defines active reading as "reading with questions in mind" , searching for the answers, and focusing on the parts of the paper that answer your questions.

Therefore, reading a scientific paper from start to finish isn't always necessary to understand it. How you read the paper depends on what you need to learn. For example, oceanographer Ken Hughes suggests that you may read a scientific paper to gain awareness of a theory or field, or you may read to actively solve a problem in your research.

To successfully read a scientific paper, we advise using three strategies:

• Identify your motivations for reading a scientific paper
• Use selective reading to gain a high-level understanding of the scientific paper
• Read straight through to achieve a deep understanding of a scientific paper .

All 3 steps require you to think critically and have questions in mind.

Before you sit down to read a scientific paper, ask yourself these three questions:

• Why do I need to read this paper?
• What information am I looking for?
• Where in the paper am I most likely to find the information I need?

Is it background reading or a literature review for a research project you are currently working on? Are you getting into a new field of research? Do you wish to compare your results with the ones presented in the paper? Are you following an author’s work, and need to keep up-to-date on their current research? Are you keeping tabs on emerging methods in your field?

All of these intentions require a different reading approach.

For example, if you're delving into a new field of research, you'll want to read the introduction to gather background information and seminal references. The discussion section will also be important to understand the broader context of the findings.

If you aim to extend the work presented in a paper, and this study will be the starting point for your work, it's crucial to read the paper deeply.

If your focus is on the study design and techniques used by the authors, you'll spend most of your time reading and understanding the methods section.

Sometimes you'll need to read a paper to discuss it in your own research. This may be to compare or contrast your work with the paper's content, or to stimulate a discussion on future applications of your work.

If you are following an author’s work, a quick skim might suffice to understand how the paper fits into their overall research program.

Tip: Knowing why you want to read the paper facilitates how you will read the paper. Depending on your needs, your approach may take the form of a surface-level reading or a deep and thorough reading.

Knowing your motivations will guide your navigation through the paper because you have already identified which sections are most likely to contain the information you need. Approaching reading a paper in this way saves you time and makes the task less daunting.

➡️ Learn more about how to write a literature review

Begin by gaining an overview of the paper by following these simple steps:

• Read the title. What type of paper is it? Is it a journal article, a review, a methods paper, or a commentary?
• Read the abstract . The abstract is a summary of the study. What is the study about? What question was addressed? What methods were used? What did the authors find, and what are the key findings? What do the authors think are the implications of the work? Reading the abstract immediately tells you whether you should invest the time to read the paper fully.
• Look at the headings and subheadings, which describe the sections and subsections of the paper. The headings and subheadings outline the story of the paper.
• Skim the introduction. An introduction has a clear structure. The first paragraph is background information on the topic. If you are new to the field, you will read this closely, whereas an expert in that field will skim this section. The second component defines the gap in knowledge that the paper aims to address. What is unknown, and what research is needed? What problem needs to be solved? Here, you should find the questions that will be addressed by the study, and the goal of the research. The final paragraph summarizes how the authors address their research question, for example, what hypothesis will be tested, and what predictions the authors make. As you read, make a note of key references. By the end of the introduction, you should understand the goal of the research.
• Go to the results section, and study the figures and tables. These are the data—the meat of the study. Try to comprehend the data before reading the captions. After studying the data, read the captions. Do not expect to understand everything immediately. Remember, this is the result of many years of work. Make a note of what you do not understand. In your second reading, you will read more deeply.
• Skim the discussion. There are three components. The first part of the discussion summarizes what the authors have found, and what they think the implications of the work are. The second part discusses some (usually not all!) limitations of the study, and the final part is a concluding statement.
• Glance at the methods. Get a brief overview of the techniques used in the study. Depending on your reading goals, you may spend a lot of time on this section in subsequent readings, or a cursory reading may be sufficient.
• Summarize what the paper is about—its key take-home message—in a sentence or two. Ask yourself if you have got the information you need.
• List any terminology you may need to look up before reading the paper again.
• Scan the reference list. Make a note of papers you may need to read for background information before delving further into the paper.

Congratulations, you have completed the first reading! You now have gained a high-level perspective of the study, which will be enough for many research purposes.

Now that you have an overview of the work and you have identified what information you want to obtain, you are ready to understand the paper on a deeper level. Deep understanding is achieved in the second and subsequent readings with note-taking and active reflection. Here is a step-by-step guide.

• Active engagement with the material
• Critical thinking
• Creative thinking
• Synthesis of information
• Consolidation of information into memory.

Highlighting sentences helps you quickly scan the paper and be reminded of the key points, which is helpful when you return to the paper later.

Notes may include ideas, connections to other work, questions, comments, and references to follow up on.

There are many ways for taking notes on a paper. You can:

• Print out the paper, and write your notes in the margins.
• Annotate the paper PDF from your desktop computer, or mobile device .
• Use personal knowledge management software, like Notion , Obsidian, or Evernote, for note-taking. Notes are easy to find in a structured database and can be linked to each other.
• Use reference management tools to take notes. Having your notes stored with the scientific papers you’ve read has the benefit of keeping all your ideas in one place. Some reference managers, like Paperpile, allow you to add notes to your papers, and highlight key sentences on PDFs .

Note-taking facilitates critical thinking and helps you evaluate the evidence that the authors present. Ask yourself questions like:

• What new contribution has the study made to the literature?
• How have the authors interpreted the results? (Remember, the authors have thought about their results more deeply than anybody else.)
• What do I think the results mean?
• Are the findings well-supported?
• What factors might have affected the results, and have the authors addressed them?
• Are there alternative explanations for the results?
• What are the strengths and weaknesses of the study?
• What are the broader implications of the study?
• What should be done next?

Note-taking also encourages creative thinking . Ask yourself questions like:

• What new ideas have arisen from reading the paper?
• How does it connect with your work?
• What connections to other papers can you make?
• Write a summary of the paper in your own words. This is your attempt to integrate the new knowledge you have gained with what you already know from other sources and to consolidate that information into memory. You may find that you have to go back and re-read some sections to confirm some of the details.
• Discuss the paper with others. You may find that even at this stage, there are still aspects of the paper that you are striving to understand. It is now a good time to reach out to others—peers in your program, your advisor, or even on social media. In their 10 simple rules for reading a scientific paper , Maureen Carey and coauthors suggest that participating in journal clubs, where you meet with peers to discuss interesting or important scientific papers, is a great way to clarify your understanding.
• A scientific paper can be read over many days. According to research presented in the book " Make it Stick: The Science of Successful Learning " by writer Peter Brown and psychology professors Henry Roediger and Mark McDaniel, "spaced practice" is more effective for retaining information than focusing on a single skill or subject until it is mastered. This involves breaking up learning into separate periods of training or studying. Applying this research to reading a scientific paper suggests that spacing out your reading by breaking the work into separate reading sessions can help you better commit the information in a paper to memory.

A dense journal article may need many readings to be understood fully. It is useful to remember that many scientific papers result from years of hard work, and the expectation of achieving a thorough understanding in one sitting must be modified accordingly. But, the process of reading a scientific paper will get easier and faster with experience.

The best way to read a scientific paper depends on your needs. Before reading the paper, identify your motivations for reading a scientific paper, and pinpoint the information you need. This will help you decide between skimming the paper and reading the paper more thoroughly.

Don’t read the paper from beginning to end. Instead, be aware of the scientific paper format. Take note of the information you need before starting to read the paper. Then skim the paper, jumping to the appropriate sections in the paper, to get the information you require.

It varies. Skimming a scientific paper may take anywhere between 15 minutes to one hour. Reading a scientific paper to obtain a deep understanding may take anywhere between 1 and 6 hours. It is not uncommon to have to read a dense paper in chunks over numerous days.

First, read the introduction to understand the main thesis and findings of the paper. Pay attention to the last paragraph of the introduction, where you can find a high-level summary of the methods and results. Next, skim the paper by jumping to the results and discussion. Then carefully read the paper from start to finish, taking notes as you read. You will need more than one reading to fully understand a dense research paper.

To read a scientific paper critically, be an active reader. Take notes, highlight important sentences, and write down questions as you read. Study the data. Take care to evaluate the evidence presented in the paper.

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How To Read A Scientific Paper In 15 Simple Steps

Navigating through a scientific paper doesn't have to be challenging. Follow these 15 steps to learn how to read a scientific paper with ease.

Table of Contents

What Is A Scientific Paper?

Introduction section, materials and methods section, results and discussion sections, conclusion section, related reading, how long does it take to read and understand a scientific paper, unriddle allows you to read faster and write better, 3 things to consider while reading a scientific paper, 1. why: the importance of reading a scientific paper, 2. how: strategies to make reading easier, 3. anatomy: understanding the components of a scientific paper, 1. pick your reading goal: how to read a scientific paper, 2. understand the author's goal: how to read and understand a scientific paper, 3. begin by reading the introduction: how to read scientific articles, 4. identify the big question: how to read a scientific paper, 5. skim the article: how to read and understand a scientific paper, 6. read the methods section: how to read a scientific paper, 7. grasp the vocabulary: how to read scientific papers, 8. read the results section: how to read a scientific paper, 9. unpack each figure and table: understanding research papers, 10. read the conclusion/discussion/interpretation section: how to read scientific articles, 11. now, go back to the beginning and read the abstract: how to read and understand a scientific paper, 12. reflect and draw your own conclusions: the art of critical thinking, 13. be critical: how to read a scientific paper, 14. read the article a second time: enhancing your comprehension, 15. use ai tools to make it easier: simplifying the reading process, complete step-by-step guide on how to use unriddle's ai research tool, interact with documents, automatic relations, citing your sources, writing with ai, chat settings, read faster & write better with unriddle for free today, unriddle: an ai-powered tool for enhancing scientific paper reading, key features of unriddle for reading scientific papers, embrace unriddle to transform your scientific paper reading experience.

• Credible Sources For Research
• How To Find Sources For A Research Paper
• Literature Search Strategy
• How To Find Research Papers

• Unriddle generates an AI assistant on top of any document so you can quickly find, summarize and understand info. No more endless skimming.
• Unriddle understands the meaning behind your writing and automatically links you to relevant things you’ve read and written about in the past.
• Highlight text and Unriddle will show you the most relevant sources from your library using AI. Never lose a citation again.
• Generate text with AI autocomplete to improve and expand your writing, with all suggestions based on the context of what you're working on.

• Interact with documents via AI so you can quickly find and understand info.
• Then start writing in a new Note and Unriddle will show you relevant content from your library as you type.
• Get started by uploading a document .
• Or read on for the full rundown.

• Model: the machine learning model used to generate responses.
• Temperature: the amount of creative license you give to the AI.
• Max length: the maximum number of words generated in a response.
• What Makes A Source Credible?
• Can Chatgpt Summarize A Pdf
• Ai Research Tools
• Can Chat Gpt Read A Pdf
• How To Summarize A Research Article
• How To Read A Research Paper
• How To Upload Pdf To Chatgpt
• Summarize Research Paper Ai
• How To Use Chatgpt To Summarize An Article
• How To Get Chat Gpt To Read A Pdf
• Ai Literature Review
• Analyse Research Paper
• How To Use Chat Gpt For Research
• Can Chat Gpt Summarize Text
• How To Read A Scholarly Article
• Ask Your Pdf Chatgpt
• How To Read A Research Paper Quickly
• By highlighting text, you can prompt Unriddle to display the most pertinent sources from your library using AI. This feature ensures that you never lose a citation again, streamlining the research process.
• Unriddle's AI-autocomplete function assists you in generating text to refine and expand your writing, with all suggestions based on the context of your work.
• Unriddle also facilitates collaboration by providing a shared workspace where multiple users can contribute and engage with the same documents in real-time.
• Ai That Reads Pdf And Answers Questions
• Ai That Reads Pdf
• Pdf Reader Extension
• Pdf Summarizer Ai
• Chatpdf Alternative
• Scholarcy Alternative
• Ai Pdf Analyzer

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How to Read a Research Paper – A Guide to Setting Research Goals, Finding Papers to Read, and More

If you work in a scientific field, you should try to build a deep and unbiased understanding of that field. This not only educates you in the best possible way but also helps you envision the opportunities in your space.

A research paper is often the culmination of a wide range of deep and authentic practices surrounding a topic. When writing a research paper, the author thinks critically about the problem, performs rigorous research, evaluates their processes and sources, organizes their thoughts, and then writes. These genuinely-executed practices make for a good research paper.

If you’re struggling to build a habit of reading papers (like I am) on a regular basis, I’ve tried to break down the whole process. I've talked to researchers in the field, read a bunch of papers and blogs from distinguished researchers, and jotted down some techniques that you can follow.

Let’s start off by understanding what a research paper is and what it is NOT!

What is a Research Paper?

A research paper is a dense and detailed manuscript that compiles a thorough understanding of a problem or topic. It offers a proposed solution and further research along with the conditions under which it was deduced and carried out, the efficacy of the solution and the research performed, and potential loopholes in the study.

A research paper is written not only to provide an exceptional learning opportunity but also to pave the way for further advancements in the field. These papers help other scholars germinate the thought seed that can either lead to a new world of ideas or an innovative method of solving a longstanding problem.

What Research Papers are NOT

There is a common notion that a research paper is a well-informed summary of a problem or topic written by means of other sources.

But you shouldn't mistake it for a book or an opinionated account of an individual’s interpretation of a particular topic.

Why Should You Read Research Papers?

What I find fascinating about reading a good research paper is that you can draw on a profound study of a topic and engage with the community on a new perspective to understand what can be achieved in and around that topic.

I work at the intersection of instructional design and data science. Learning is part of my day-to-day responsibilities. If the source of my education is flawed or inefficient, I’d fail at my job in the long term. This applies to many other jobs in Science with a special focus on research.

There are three important reasons to read a research paper:

• Knowledge —  Understanding the problem from the eyes of someone who has probably spent years solving it and has taken care of all the edge cases that you might not think of at the beginning.
• Exploration —  Whether you have a pinpointed agenda or not, there is a very high chance that you will stumble upon an edge case or a shortcoming that is worth following up. With persistent efforts over a considerable amount of time, you can learn to use that knowledge to make a living.
• Research and review —  One of the main reasons for writing a research paper is to further the development in the field. Researchers read papers to review them for conferences or to do a literature survey of a new field. For example, Yann LeCun’ s paper on integrating domain constraints into backpropagation set the foundation of modern computer vision back in 1989. After decades of research and development work, we have come so far that we're now perfecting problems like object detection and optimizing autonomous vehicles.

Not only that, with the help of the internet, you can extrapolate all of these reasons or benefits onto multiple business models. It can be an innovative state-of-the-art product, an efficient service model, a content creator, or a dream job where you are solving problems that matter to you.

Goals for Reading a Research Paper — What Should You Read About?

The first thing to do is to figure out your motivation for reading the paper. There are two main scenarios that might lead you to read a paper:

• Scenario 1 —  You have a well-defined agenda/goal and you are deeply invested in a particular field. For example, you’re an NLP practitioner and you want to learn how GPT-4 has given us a breakthrough in NLP. This is always a nice scenario to be in as it offers clarity.
• Scenario 2 —  You want to keep abreast of the developments in a host of areas, say how a new deep learning architecture has helped us solve a 50-year old biological problem of understanding protein structures. This is often the case for beginners or for people who consume their daily dose of news from research papers (yes, they exist!).

If you’re an inquisitive beginner with no starting point in mind, start with scenario 2. Shortlist a few topics you want to read about until you find an area that you find intriguing. This will eventually lead you to scenario 1.

ML Reproducibility Challenge

In addition to these generic goals, if you need an end goal for your habit-building exercise of reading research papers, you should check out the ML reproducibility challenge.

You’ll find top-class papers from world-class conferences that are worth diving deep into and reproducing the results.

They conduct this challenge twice a year and they have one coming up in Spring 2021. You should study the past three versions of the challenge, and I’ll write a detailed post on what to expect, how to prepare, and so on.

Now you must be wondering – how can you find the right paper to read?

How to Find the Right Paper to Read

In order to get some ideas around this, I reached out to my friend, Anurag Ghosh who is a researcher at Microsoft. Anurag has been working at the crossover of computer vision, machine learning, and systems engineering.

Here are a few of his tips for getting started:

• Always pick an area you're interested in.
• Read a few good books or detailed blog posts on that topic and start diving deep by reading the papers referenced in those resources.
• Look for seminal papers around that topic. These are papers that report a major breakthrough in the field and offer a new method perspective with a huge potential for subsequent research in that field. Check out papers from the morning paper or C VF - test of time award/Helmholtz prize (if you're interested in computer vision).
• Check out books like Computer Vision: Algorithms and Applications by Richard Szeliski and look for the papers referenced there.
• Have and build a sense of community. Find people who share similar interests, and join groups/subreddits/discord channels where such activities are promoted.

In addition to these invaluable tips, there are a number of web applications that I’ve shortlisted that help me narrow my search for the right papers to read:

• r/MachineLearning  — there are many researchers, practitioners, and engineers who share their work along with the papers they've found useful in achieving those results.

• Arxiv Sanity Preserver  — built by Andrej Karpathy to accelerate research. It is a repository of 142,846 papers from computer science, machine learning, systems, AI, Stats, CV, and so on. It also offers a bunch of filters, powerful search functionality, and a discussion forum to make for a super useful research platform.

• Google Research  — the research teams at Google are working on problems that have an impact on our everyday lives. They share their publications for individuals and teams to learn from, contribute to, and expedite research. They also have a Google AI blog that you can check out.

How to Read a Research Paper

After you have stocked your to-read list, then comes the process of reading these papers. Remember that NOT every paper is useful to read and we need a mechanism that can help us quickly screen papers that are worth reading.

To tackle this challenge, you can use this Three-Pass Approach by S. Keshav . This approach proposes that you read the paper in three passes instead of starting from the beginning and diving in deep until the end.

The three pass approach

• The first pass —  is a quick scan to capture a high-level view of the paper. Read the title, abstract, and introduction carefully followed by the headings of the sections and subsections and lastly the conclusion. It should take you no more than 5–10 mins to figure out if you want to move to the second pass.
• The second pass —  is a more focused read without checking for the technical proofs. You take down all the crucial notes, underline the key points in the margins. Carefully study the figures, diagrams, and illustrations. Review the graphs, mark relevant unread references for further reading. This helps you understand the background of the paper.
• The third pass —  reaching this pass denotes that you’ve found a paper that you want to deeply understand or review. The key to the third pass is to reproduce the results of the paper. Check it for all the assumptions and jot down all the variations in your re-implementation and the original results. Make a note of all the ideas for future analysis. It should take 5–6 hours for beginners and 1–2 hours for experienced readers.

Tools and Software to Keep Track of Your Pipeline of Papers

If you’re sincere about reading research papers, your list of papers will soon grow into an overwhelming stack that is hard to keep track of. Fortunately, we have software that can help us set up a mechanism to manage our research.

Here are a bunch of them that you can use:

• Mendeley [not free]  — you can add papers directly to your library from your browser, import documents, generate references and citations, collaborate with fellow researchers, and access your library from anywhere. This is mostly used by experienced researchers.

• Zotero [free & open source] —  Along the same lines as Mendeley but free of cost. You can make use of all the features but with limited storage space.

• Notion —  this is great if you are just starting out and want to use something lightweight with the option to organize your papers, jot down notes, and manage everything in one workspace. It might not stand anywhere in comparison with the above tools but I personally feel comfortable using Notion and I have created this board to keep track of my progress for now that you can duplicate:

⚠️ Symptoms of Reading a Research Paper

Reading a research paper can turn out to be frustrating, challenging, and time-consuming especially when you’re a beginner. You might face the following common symptoms:

• You might start feeling dumb for not understanding a thing a paper says.
• Finding yourself pushing too hard to understand the math behind those proofs.
• Beating your head against the wall to wrap it around the number of acronyms used in the paper. Just kidding, you’ll have to look up those acronyms every now and then.
• Being stuck on one paragraph for more than an hour.

Here’s a complete list of emotions that you might undergo as explained by Adam Ruben in this article .

Key Takeaways

We should be all set to dive right in. Here’s a quick summary of what we have covered here:

• A research paper is an in-depth study that offers an detailed explanation of a topic or problem along with the research process, proofs, explained results, and ideas for future work.
• Read research papers to develop a deep understanding of a topic/problem. Then you can either review papers as part of being a researcher, explore the domain and the kind of problems to build a solution or startup around it, or you can simply read them to keep abreast of the developments in your domain of interest.
• If you’re a beginner, start with exploration to soon find your path to goal-oriented research.
• In order to find good papers to read, you can use websites like arxiv-sanity, google research, and subreddits like r/MachineLearning.
• Reading approach — Use the 3-pass method to find a paper.
• Keep track of your research, notes, developments by using tools like Zotero/Notion.
• This can get overwhelming in no time. Make sure you start off easy and increment your load progressively.

Remember: Art is not a single method or step done over a weekend but a process of accomplishing remarkable results over time.

You can also watch the video on this topic on my YouTube channel :

Feel free to respond to this blog or comment on the video if you have some tips, questions, or thoughts!

If this tutorial was helpful, you should check out my data science and machine learning courses on Wiplane Academy . They are comprehensive yet compact and helps you build a solid foundation of work to showcase.

Web and Data Science Consultant | Instructional Design

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How the Science of Reading Informs 21st‐Century Education

The science of reading should be informed by an evolving evidence base built upon the scientific method. Decades of basic research and randomized controlled trials of interventions and instructional routines have formed a substantial evidence base to guide best practices in reading instruction, reading intervention, and the early identification of at-risk readers. The recent resurfacing of questions about what constitutes the science of reading is leading to misinformation in the public space that may be viewed by educational stakeholders as merely differences of opinion among scientists. Our goals in this paper are to revisit the science of reading through an epistemological lens to clarify what constitutes evidence in the science of reading and to offer a critical evaluation of the evidence provided by the science of reading. To this end, we summarize those things that we believe have compelling evidence, promising evidence, or a lack of compelling evidence. We conclude with a discussion of areas of focus that we believe will advance the science of reading to meet the needs of all children in the 21st century.

For more than 100 years, the question of how best to teach children to read has been debated in what has been termed the “reading wars”. The debate cyclically fades into the background only to reemerge, often with the same points of conflict. We believe that this cycle is not helpful for promoting the best outcomes for children’s educational success. Our goal in this paper is to make an honest and critical appraisal of the science of reading, defining what it is, how we build a case for evidence, summarizing those things for which the science of reading has provided unequivocal answers, providing a discussion of things we do not know but that may have been “oversold,” identifying areas for which evidence is promising but not yet compelling, and thinking ahead about how the science of reading can better serve all stakeholders in children’s educational achievements.

At its core, scientific inquiry is the same in all fields. Scientific research, whether in education, physics, anthropology, molecular biology, or economics, is a continual process of rigorous reasoning supported by a dynamic interplay among methods, theories, and findings. It builds understandings in the form of models or theories that can be tested. Advances in scientific knowledge are achieved by the self-regulating norms of the scientific community over time, not, as sometimes believed, by the mechanistic application of a particular scientific method to a static set of questions (National Research Council, 2002, p. 2).

What is the Science of Reading and Why are we Still Debating it?

The “science of reading” is a phrase representing the accumulated knowledge about reading, reading development, and best practices for reading instruction obtained by the use of the scientific method. We recognize that the accrual of scientific knowledge related to reading is ever evolving, at times circuitous, and not without controversy. Nonetheless, the knowledge base on the science of reading is vast. In the last decade alone, over 14,000 peer-reviewed articles have been published in journals that included the keyword “reading” based on a PsycINFO search. Although many of these studies likely focused on a sliver of the reading process individually, collectively, research studies with a focus on reading have yielded a substantial knowledge base of stable findings based on the science of reading. Taken together, the science of reading helps a diverse set of educational shareholders across institutions (e.g., preschools, schools, universities), communities, and families to make informed choices about how to effectively promote literacy skills that foster healthy and productive lives ( DeWalt & Hink, 2009 ; Rayner et al., 2001 ).

An interesting question concerning the science of reading is “Why is there a debate surrounding the science of reading?” Although there are certainly disputes within the scientific community regarding best practices and new areas of research inquiry, most of the current debate seems to settle upon what constitutes scientific evidence, how much value we should place on scientific evidence as opposed to other forms of knowledge, and how preservice teachers should be instructed to teach reading ( Brady, 2020 ). The current disagreement in what constitutes the scientific evidence of reading (e.g., Calkins, 2020 ) is not new. During the last round of the “reading wars” in the late 1990’s and early 2000’s these same issues were discussed and debated. Much of the debate focused on conflicting views in epistemology between constructivists and positivists on the basic mechanisms associated with reading development. Constructivists, such as Goodman (1967) and Smith (1971) , believed that reading was a “natural act” akin to learning language and thus emphasized giving children the opportunity to discover meaning through experiences in a literacy-rich environment. In contrast, positivists, such as Chall (1967) and Flesch (1955) , made strong distinctions between innate language learning and the effortful learning required to acquire reading skills. Positivists argued for explicit instruction to help foster understanding of how the written code mapped onto language, whereas constructivists encouraged children to engage in a “psycholinguistic guessing game” in which readers use their graphic, semantic, and syntactic knowledge (known as the three cuing system) to guess the meaning of a printed word.

Research clearly indicates that skilled reading involves the consolidation of orthographic and phonological word forms ( Dehene, 2011 ). Work in cognitive neuroscience indicates that a small region of the left ventral visual cortex becomes specialized for this purpose. As children learn to read, they recruit neurons from a small region of the left ventral visual cortex within the left occipitotemporal cortex region (i.e., visual word form area) that are tuned to language-dependent parameters through connectivity to perisylvian language areas ( Dehaene-Lambertz et al., 2018 ). This provides an efficient circuit for grapheme-phoneme conversion and lexical access allowing efficient word-reading skills to develop. These studies provide direct evidence for how teaching alters the human brain by repurposing some visual regions toward the shapes of letters, suggesting that cultural inventions, such as written language, modify evolutionarily older brain regions. Furthermore, studies suggest that instruction focusing on the link between orthography and phonology promote this brain reorganization (e.g., Dehaene, 2011 ). Yet, arguments between philosophical constructivists and philosophical positivists on what constitutes the science of reading and how it informs instruction remain active today (e.g., Castles et al., 2018 ). In a recent interview with Emily Hanford, Ken Goodman defended his advocacy for the three cuing system saying that the three-cueing theory is based on years of observational research. In his view, three cueing is perfectly valid, drawn from a different kind of evidence than what scientists collect in their lab and later he stated that “my science is different” ( Hanford, 2019 ).

As scientists at the Florida Center for Reading Research, we are often frustrated when what we view to be the empirically supported evidence base about the reading process are distorted or denied in communications directed to the public and to teachers. However, Stanovich (2003) posited that “in many cases, the facts are secondary—what is being denied are the styles of reasoning that gave rise to the facts; what is being denied is closer to a worldview than an empirical finding. Many of these styles are implicit; we are not conscious of them as explicit rules of behavior” (pp. 106-107). Stanovich proposed five different dimensions that represent “styles” of generating knowledge about reading. For our purposes, here, we focus on the first dimension: the correspondence versus coherence theory of truth. It hits at the heart of how people believe something to be true. People who believe that a real world exists independent of their beliefs, and that interrogating this world using rigorous principles to gain knowledge is a fruitful activity are said to subscribe to the correspondence theory of truth. In contrast, those who subscribe to the coherence theory of truth believe that something is “true” if the beliefs about something fit together in a logical way. In essence, something is true if it makes sense.

Stanovich believed these differing truth systems might lie at the heart of the disagreements surrounding the science of reading. One side shouting, “Look at this mountain of evidence! How can you not believe it?” and the other side shouting, “It doesn’t make sense! It doesn’t match up with our experiences! Why should we value your knowledge above our own?!” By approaching the science of reading from the perspective of the correspondence theory of truth, we consider how compelling evidence can be generated, what we believe is the compelling evidence, what we think lacks evidence, and what we think is promising evidence.

How We Build a Case for Compelling Evidence

Research is the means by which we acquire and understand knowledge about the world ( Dane, 1990 ) to create scientific principles. Relatively few scientists would argue with the importance of using research evidence to support a principle or to make claims about reading development and the quality of reading instruction. Where significant divergence often occurs is in response to policy statements that categorize research claims and instructional strategies into those with greater or lesser levels of evidence. This divergence is typically rooted in applied epistemology, which can be understood as the study of whether the means by which we study evidence are themselves well designed to lead to valid conclusions. Researchers often frame the science of reading from divergent applied epistemological perspectives. Thus, two scientists who approach the science of reading with different epistemologies will both suggest that they have principled understandings and explanations for how children learn to read; yet, the means by which those understandings and explanations were derived are often distinct.

The correspondence and coherence theories of truth described above are examples of explanations from contrasting epistemological perspectives. Consistent with these perspectives, researchers approaching the science of reading using a correspondence theory typically prioritize deductive methods, which embed hypothesis testing, precise operationalization of constructs, and efforts to decouple the researchers’ beliefs from their interpretation and generalization of empirical evidence. Researchers approaching the science of reading using a coherence theory of truth typically prioritize more inductive methods, such as phenomenological, ethnographic, and grounded theory approaches that embed focus on the meaning and understanding that comes through a person’s lived experience and where the scientist’s own observations shape meaning and principles (e.g., Israel & Duffy, 2014 ).

When the National Research Council published Scientific Research in Education (2002), a significant amount of criticism levied against the report boiled down to differences in epistemological perspectives. Yet, these genuine contrasts can often obscure contributions to the science of reading that derive from multiple applied epistemologies. Observational research, using both inductive (e.g., case studies) and deductive (e.g., correlational studies) approaches, substantively informs the development of theories and of novel instructional approaches (e.g., Scruggs et al., 2007 ). Public health research offers a useful parallel. As it would be unethical to establish a causal link from smoking cigarettes to lung cancer through a randomized controlled trial, that field instead used well-designed observational studies to derive claims and principles. These findings then informed later stages in the broader program of research, including randomized controlled trials of interventions for smoking cessation.

In the science of reading, principles and instructional strategies should indeed capitalize on a program of research inclusive of multiple methodologies. Yet, as the public health domain ultimately takes direction from the efficacy of smoking cessation programs, so too must the science of reading take direction from theoretically informed and well-designed experimental and quasi-experimental studies of promising strategies when the intention is to evaluate instructional practices. The use of experimental (i.e., randomized trials) and quasi-experimental (e.g., regression discontinuity, propensity score matching, interrupted time series) designs, in which an intervention is competed against counterfactual conditions, such as typical practice or alternative interventions, provides the strongest causal credibility regarding which instructional strategies are effective. The What Works Clearinghouse (WWC) of the Institute of Education Sciences (e.g., What Works Clearinghouse, 2020) and the Every Student Succeeds Act (ESSA; Every Student Succeeds Act, 2015 ) are efforts by the US Department of Education to hierarchically characterize the levels of evidence currently available for instructional practices in education. The WWC uses a review framework, developed by methodological and statistical experts, for evaluating the quality and scope of evidence for specific instructional practices based on features of the design, implementation, and analysis of studies. Similarly, ESSA uses four tiers that focus on both the design of the study and the results of the study in which the tiers differ based on the quantity of evidence and quality of evidence supporting an approach. For both WWC and ESSA, quantity of evidence refers to the number of well-designed and well-implemented studies, and quality of evidence is defined by the ability of a study’s methods to allow for alternative explanations of a finding to be ruled out, for which the randomized controlled trial provides the strongest method.

As outlined above, the “science of reading” utilizes multiple research approaches to generate ideas about reading. Ultimately, the highest priority in the science of reading should be the replicable and generalizable knowledge from observational and experimental methods, rooted in a deductive research approach to knowledge generation that is framed in a correspondence theory of truth. In this manner, the accumulated evidence is built on a research foundation by which theories, principles, and hypotheses have been subjected to rigorous empirical scrutiny to determine the degree to which they hold up across variations in samples, measures, and contexts. In the following sections, we summarize issues related to the nature, development, and instruction of reading for which we believe the science of reading either has or has not yielded compelling evidence, identify what we believe are promising areas for which sufficient evidence has not yet accumulated, and suggest a number of areas that we believe will help move the science of reading forward, increasing knowledge and enhancing its positive impacts for a variety of stakeholders.

Compelling Evidence in the Science of Reading

In this section, we focus on a number of findings centrally important for understanding the development and teaching of reading in alphabetic languages. The evidence base provides answers varying across orthographic regularity (e.g., English vs. Spanish), reading subskill (i.e., decoding vs. comprehension), grade range or developmental level (e.g., early childhood, elementary, adolescence), and linguistic diversity (e.g., English language learners, dialect speakers).

There are large differences among alphabetic languages in the rules for how graphemes represent sounds in words (i.e., a language’s orthography). In languages like Spanish and Finnish there is a near one-to-one relation between letters and sounds. The letter-sound coding in these languages is transparent, and they have shallow orthographies. In other languages, most notably English, there is often not a one-to-one relation between letters and sounds. The letter-sound coding in these languages is opaque, and they have deep orthographies. Children must learn which words cannot be decoded based solely on letter-sound correspondence (e.g., two, knight, laugh) and learn to match these irregular spellings to the words they represent. Where a language’s orthography falls on the shallow-deep dimension affects how quickly children develop accurate and fluent word-reading skills ( Ellis et al., 2004 ; Ziegler & Goswami, 2005 ) and how much instruction on foundational reading skills is likely needed. Studies indicate that children learning to read in English are slower to acquire decoding skills (e.g., Caravolas et al., 2013 ). Ziegler et al. (1997) reported that 69% of monosyllabic words in English were consistent in spelling-to-phonology mappings and 31% of the phonology-to-spelling mappings were consistent. Thus, in teaching children to read in English, the “grain size” of phoneme, onset-rime, and whole word matters ( Ziegler & Goswami, 2005 ) and the preservation of morphological regularities in English spelling matters (e.g., vine vs. vineyard ).

Gough and Tunmer’s (1986) “simple view of reading” model, which is supported by a significant amount of research, provides a useful framework for conceptualizing the development of reading skills across time. It also frames the elements for which it is necessary to provide instructional support. The ultimate goal of reading is to extract and construct meaning from text for a purpose. For this task to be successful, however, the reader needs skills in both word decoding and linguistic comprehension. Weaknesses in either area will reduce the capacity to achieve the goal of reading. Decoding skills and linguistic comprehension make independent contributions to the prediction of reading comprehension across diverse populations of readers ( Kershaw & Schatschneider, 2012 ; Sabatini et al., 2010 ; Vellutino, et al., 2007 ). Results of several studies employing measurement strategies that allow modeling of each component as a latent variable indicate that decoding and linguistic comprehension account for almost all of the variance in reading comprehension (e.g., Foorman et al., 2015 ; Lonigan et al., 2018 ). The relative influence of these skill domains, however, changes across development. The importance of decoding skill in explaining variance in reading comprehension decreases across grades whereas the importance of linguistic comprehension increases (e.g., Catts et al., 2005 ; Foorman et al., 2018 ; García & Cain, 2014 ; Lonigan et al., 2018 ). By the time children are in high school linguistic comprehension and reading comprehension essentially form a single dimension (e.g., Foorman et al., 2018 ).

Children’s knowledge of the alphabetic principle (i.e., how letters and sounds connect) and knowledge of the morphophonemic nature of English are necessary to create the high-quality lexical representations essential to accurate and efficient decoding ( Ehri, 2005 ; Perfetti, 2007 ). Acquiring the alphabetic principle is dependent on understanding that words are composed of smaller sounds (i.e., phonological awareness, PA) and alphabet knowledge (AK). Both PA and AK are substantial correlates and predictors of decoding skills (e.g., Wagner & Torgesen, 1987 ; Wagner et al., 1994 ). Prior to formal reading instruction, children are developing PA and AK as well as other early literacy skills that are related to later decoding skills following formal reading instruction ( Lonigan et al., 2009 ; Lonigan et al., 1998 ; National Early Literacy Panel [NELP], 2008 ; Whitehurst & Lonigan, 1998 ). Reading comprehension takes advantage of the reader’s ability to understand language. In most languages, written language and spoken language have high levels of overlap in their basic structure. Longitudinal studies indicate that linguistic comprehension skills from early childhood predict reading comprehension at the end of elementary school ( Catts et al., 2015 ; Language and Reading Research Consortium & Chiu, 2018 ; Mancilla-Martinez & Lesaux, 2010 ; Storch & Whitehurst, 2002 ; Verhoeven & Van Leeuwe, 2008 ). The developmental precursors to skilled reading are present prior to school entry. Consequently, differences between children in the development of these skills forecast later differences in reading skills and are useful for identifying children at risk for reading difficulties.

The science of reading provides numerous clear answers about the type and focus of reading instruction for the subskills of reading, depending on where children are on the continuum of reading development and children’s linguistic backgrounds. Much of this knowledge is summarized in the practice guides produced by the Institute of Education Sciences ( Baker et al., 2014 ; Foorman et al., 2016a ; Gersten et al., 2007 , 2008 ; Kamil et al., 2008 ; Shanahan et al., 2010 ) and in meta-analytic summaries of research (e.g., Berkeley et al., 2012 ; Ehri, Nunes, Stahl et al., 2001 ; Ehri, Nunes, Willows et al., 2001 ; NELP, 2008 ; Therrien, 2004 ; Wanzek et al., 2013 , 2016 ). Whereas the practice guides list several best practices, here we emphasize those practices classified as supported by strong or moderate evidence based on WWC standards.

Since the publication of the Report of the National Reading Panel ( National Institute of Child Health and Human Development, 2000 ) and supported by subsequent research (e.g., Gersten et al., 2017a ; Foorman et al., 2016a ), it is clear that a large evidence base provides strong support for the explicit and systematic instruction of the component and foundational skills of decoding and decoding itself. That is, teaching children phonological awareness and letter knowledge, particularly when combined, results in improved word-decoding skills. Teaching children to decode words using systematic and explicit phonics instruction results in improved word-decoding skills. Such instruction is effective both for monolingual English-speaking children and children whose home language is other than English (i.e., dual-language learners; Baker et al., 2014 ; Gersten et al., 2007 ) as well as children who are having difficulties learning to read or who have an identified reading disability ( Ehri, Nunes, Stahl et al., 2001 ; Gersten et al., 2008 ). Additionally, providing children with frequent opportunities to read connected text supports the development of word-reading accuracy and fluency as well as comprehension skills ( Foorman et al., 2016a ; Therrien, 2004 ).

Similarly, a number of instructional activities to promote the development of reading comprehension have strong or moderate supporting evidence. For younger children, teaching children how to use comprehension strategies and how to utilize the organizational structure of a text to understand, learn, and retain content supports better reading comprehension ( Shanahan et al., 2010 ). For older children, teaching the use of comprehension strategies also enhances reading comprehension ( Kamil et al., 2008 ) as does explicit instruction in key vocabulary, providing opportunities for extended discussion of texts, and providing instruction on foundational reading skills when children lack these skills; such instructional approaches are also effective for children with significant reading difficulties ( Berkeley et al., 2012 ; Kamil et al., 2008 ).

Lack of Compelling Evidence in the Science of Reading

In the above section, practices were highlighted that have sufficient evidence to warrant their widespread use. In this section, we address reading practices for which there is a lack of compelling evidence. Some practices have simply not yet been scientifically evaluated. Other practices have been evaluated, but either the evidence does not support their use based on the generalizability of the results or the studies in which they were evaluated were not of sufficient quality to meet a minimal standard of evidence (e.g., WWC standards). Although we lack sufficient space to present a comprehensive list of practices that do not have compelling evidence, we provide examples of practices that are commonplace and vary in the degree to which they have been scientifically studied.

Evidence-based decision making regarding effective literacy programs and practices for classroom use can be difficult. Often, there is no evidence of effectiveness for a program or the evidence is of poor quality. For instance, of the five most popular reading programs used nationwide (i.e., Units of Study for Teaching Reading, Journeys, Into Reading, Leveled Literacy Intervention and Reading Recovery; Schwartz, 1999) only Leveled Literacy Intervention and Reading Recovery, both interventions for struggling readers, have studies that meet WWC standards. The evidence indicates that there were mixed effects across outcomes for Leveled Literacy Intervention and positive or potentially positive effects for Reading Recovery (e.g., Chapman & Tunmer, 2016 ). Classroom reading programs are typically built around the notion of evidence-informed practices – teaching approaches that are grounded in quality research – but have not been subjected to direct scientific evaluation. As a consequence, it is currently impossible for schools to select basal reading programs that adhere to strict evidence-based standards (e.g., ESSA, 2015 ). As an alternative, schools must develop selection criteria for choosing classroom reading programs informed by the growing scientific evidence on instructional factors that support early reading development (e.g., Castles et al., 2018 ; Foorman et al.2017 ; Rayner et al., 2001 ).

Common instructional approaches that lack generalizable empirical support include such practices as close reading ( Welsch et al., 2019 ), use of decodable text ( Jenkins et al., 2004 ), sustained silent reading ( NICHD, 2000 ), multisensory approaches ( Birsh, 2011 ), and the three-cueing system to support word recognition development (Seidenberg, 2017). Some of these instructional approaches rest on sound theoretical and pedagogical grounds. For example, giving beginning readers the opportunity to read decodable texts provides practice applying the grapheme-phoneme relations they have learned to successfully decode words ( Foorman et al., 2016a ), thus building lexical memory to support word reading accuracy and automaticity (Ehri, this issue). However, the only study to experimentally examine the impact of reading more versus less decodable texts as part of an early intervention phonics program for at risk first graders found no differences between the two groups on any of the posttest measures ( Jenkins et al., 2004 ). Such a result does not rule out the possibility of the usefulness of decodable texts but rather indicates the need to disentangle the active ingredients of effective interventions to specify what to use, when, how often, and for whom.

Similarly, multisensory approaches (e.g., Orton-Gillingham) that teach reading by using multiple senses (i.e., sight, hearing, touch, and movement) to help children make systematic connections between language, letters, and words ( Birsh, 2011 ) are commonplace and have considerable clinical support for facilitating reading development in children who struggle to learn to read. However, there is little scientific evidence that indicates that a multisensory approach is more effective than similarly structured phonological-based approaches that do not include a strong multisensory component (e.g., Boyer & Ehri, 2011 ; Ritchey & Goeke, 2006 ; Torgesen et al., 2001 ). With further research, we may find that a multisensory component is a critical ingredient of intervention for struggling readers, but we lack this empirical evidence currently.

Instruction in reading comprehension is another area where despite some studies showing moderate or strong support (see section on compelling evidence) other practices are employed despite limited support for them (e.g., Boulay et al., 2015 ). The complexity of reading comprehension relies on numerous cognitive resources and background knowledge; as a result, intervention directed exclusively at one component or another is not likely to be that impactful. For example, research shows a clear relation between breadth and depth of vocabulary and reading comprehension ( Wagner et al., 2007 ). One implication of this relation is that teaching vocabulary could improve reading comprehension. Numerous studies have tested this implication using instructional approaches that vary from teaching words in isolation to practices that involve instruction in the use of context to learn the meaning of unfamiliar words. Instruction has also included strategies to determine meaning of words through word study and morphological analysis (e.g., Beck & McKeown, 2007 ; Lesaux et al., 2014 ). Although these practices have been effective in increasing vocabulary knowledge of the words taught, there is limited evidence of transfer to untaught words (as measured by standardized measures) or to improvement in general reading comprehension ( Elleman et al., 2009 ; Lesaux et al., 2010 ). Such findings do not mean that vocabulary instruction is not a useful practice; rather, by itself, it is not sufficient to improve reading comprehension. To make meaningful gains, intervention for reading comprehension likely requires addressing multiple components of language as well as teaching content knowledge (see next section) to make sizable gains.

Other instructional practices go directly against what is known from the science of reading. For example, the three-cueing approach to support early word recognition (i.e., relying on a combination of semantic, syntactic, and graphophonic cues simultaneously to formulate an intelligent hypothesis about a word’s identity) ignores 40 years of overwhelming evidence that orthographic mapping involves the formation of letter-sound connections to bond spelling, pronunciation, and meaning of specific words in memory (see Ehri, this issue). Moreover, relying on alternative cuing systems impedes the building of automatic word-recognition skill that is the hallmark of skilled word reading ( Stanovich, 1990 ; 1991 ). The English orthography, being both alphabetic-phonemic and morpho-phonemic, clearly privileges the use of various levels of grapheme-phoneme correspondences to read words ( Frost, 2012 ), with rapid context-free word recognition being the process that most clearly distinguishes good from poor readers ( Perfetti, 1992 ; Stanovich, 1980 ). Guessing at a word amounts to a lost learning trial to help children learn the orthography of the word and thus reduce the need to guess the word in the future ( Castles et al., 2018 ; Share, 1995 ).

Similarly, alternative approaches to improving reading skills for struggling readers often fall well outside the scientific consensus regarding sources of reading difficulties. Some of these approaches are based on the tenet that temporal processing deficits in the auditory (e.g., Tallal, 1984 ) and visual (e.g., Stein, 2019 ) systems of the brain are causally related to poor word-reading development. Although there is some evidence that typically developing and struggling readers differ on measures tapping auditory ( Casini et al., 2018 ; Protopapas, 2014 ) and visual (e.g., Eden et al., 1995; Olson & Datta, 2002 ) processing skill, there is little evidence to support the use of instructional programs designed to improve auditory or visual systems to ameliorate reading problems ( Strong et al., 2011 ). Further, interventions designed to decrease visual confusion (e.g., Dyslexie font) or modify transient channel processing (e.g., Irlen lenses) to improve reading skill for children with reading disability have also failed to garner scientific support ( Hyatt et al., 2009 ; Iovino et al., 1998 ; Marinus et al., 2016 ). Similarly, although use of video games to improve reading via enhanced visual attention is reported to be an effective intervention for children with reading disability ( Peters et al., 2019 ), studies of this supplemental intervention approach have not compared it to standard supplemental approaches. Finally, studies of interventions designed to enhance other cognitive processes, such as working memory, also lack evidence effectiveness in terms of improved reading-related outcomes (e.g., Melby-Lervåg et al., 2016 ).

Promising but Not (Yet) Compelling Evidence in the Science of Reading

There are many promising areas of research that are poised to provide compelling evidence to inform the science of reading in the coming years. As we do not have space to provide a comprehensive list, we highlight only a few promising areas in prevention research and elementary education research.

Promising Directions in Prevention Research

Research on the prevention of reading problems is critical for our ability to reduce the number of children who struggle learning to read. One area of prevention research that has great promise but needs more evidence is how to more fully develop preschoolers’ language abilities that support later reading success. Both correlational and experimental findings indicate that providing children with opportunities to engage in high-quality conversations, coupled with exposure to advanced language models, matters for language development ( Cabell et al., 2015 ; Dickinson & Porche, 2011 ; Lonigan et al., 2011 ; Wasik & Hindman, 2018). Yet, most programs have a more robust impact on children’s proximal language learning (i.e., learning taught words) than on generalized language learning as measured with standardized assessments ( Marulis & Neuman, 2010 ).

Promising studies that have demonstrated significant effects on children’s general language development elucidate potential points of leverage. First, improving the connection between the school and home contexts by including parents as partners can promote synergistic learning for children as language-learning activities in school and home settings are increasingly aligned (e.g., Lonigan & Whitehurst, 1998 ). A second leverage point is increasing attention to children’s active use of language in the classroom to promote a rich dialogue between children and adults (e.g., Lonigan et al., 2011 ; Wasik & Hindman, 2018). A third leverage point is integrating content area instruction into early literacy instruction to improve language learning, for example, building children’s conceptual knowledge of the social and natural world and teaching vocabulary words within the context of related ideas (e.g., Gonzalez et al., 2011 ).

Promising Directions in Elementary Education Research

We present two promising areas in reading research with elementary-age students, one focused on improving linguistic comprehension and one focused on improving decoding, consistent with the simple view of reading.

The knowledge a reader brings to a text is the chief determinant of whether the reader will understand that text ( Anderson & Pearson, 1984 ). Thus, building knowledge is an essential, yet neglected, part of improving linguistic comprehension (Cabell & Hwang, this issue). Teaching reading is most often approached in early elementary classrooms as a subject that is independent from other subjects, such as science and social studies ( Palinscar & Duke, 2004 ). As such, reading is taught using curricula that do not systematically build children’s knowledge of the social and natural world. Instruction in reading and the content areas does not have to be an either/or proposition. Rather, the teaching of reading and of content-area learning can be simultaneously taught and integrated to powerfully impact children’s learning of both reading and content knowledge (e.g., Connor et al., 2017 ; Kim et al., 2020 ; Williams et al., 2014 ). This area of research is promising but not yet compelling, due to the small number of experimental and quasi-experimental studies that have examined either integrated content-area and literacy instruction or content-rich English Language Arts instruction in K-5 settings (approximately 31 studies). Through meta-analysis, this corpus of studies demonstrates that combining knowledge building and literacy approaches has a positive impact on both vocabulary and comprehension outcomes for elementary-age children ( Hwang et al., 2019 ). Further rigorous studies are needed that test widely used content-rich English Language Arts curricula (Cabell & Hwang, 2020, this issue); also required is new development of integrative and interdisciplinary approaches in this area.

There is also promising research on helping students to decode words more efficiently. It is widely accepted that students with reading difficulties often have underlying deficits in phonological processing (e.g., Brady & Schankweiler, 1991 ; Stanovich & Siegel, 1994 ; Torgesen, 2000 ; Vellutino et al., 1996 ) and these deficits are believed to disrupt the acquisition of spelling-to-sound translation routines that form the basis of early decoding-skill development (e.g., van IJzendoorn & Bus, 1994 ; Rack et al., 1992 ). For developing readers, decoding an unfamiliar letter string can result in either full or partial decoding. During partial decoding, the reader must match the assembled phonology from decoding with their lexical representation of a word ( Venezky, 1999 ). For example, encountering the word island might render the incorrect but partial decoding attempt, “izland”. A child’s flexibility with the partially decoded word is referred to as their “set for variability” or their ability to go from the decoded form to the correct pronunciation of a word. This skill serves as a bridge between decoding and lexical pronunciations and may be an important second step in the decoding process ( Elbro et al., 2012 ).

The matching of partial phonemic-decoding output is facilitated by the child’s decoding skills, the quality of the child’s lexical word representation, and by the potential contextual support of text ( Nation & Castles, 2017 ). Correlational studies indicate that students’ ability to go from a decoded form of a word to a correct pronunciation (their set for variability) predicts the reading of irregular words ( Tunmer & Chapman, 2012 ), regular words ( Elbro, et al., 2012 ), and nonwords ( Steacy et al., 2019a ). Set for variability has also been found to be a stronger predictor of word reading than phonological awareness in students in grades 2-5 (e.g., Steacy et al., 2019b ). Recent studies in this area suggest that children can benefit from being encouraged to engage with the irregularities of English ( Dyson et al., 2017 ) to promote the implicit knowledge structures needed to read and spell these complex words. Additional research suggests that set for variability training can be effective in promoting early word reading skills (e.g., Savage et al., 2018 ; Zipke, 2016 ). The work done in this area to date suggests that set for variability requires child knowledge structures and strategies, which can be developed through instruction, that allow successful matching of partial phonemic-decoding output with the corresponding phonological, morphological, and semantic lexical representations.

Where Do We Go Next in the Science of Reading?

Basic science research.

The science of reading has reached some consensus on the typical development of reading skill and how individual differences may alter this trajectory (e.g., Boscardin et al., 2008 ; Hjetland et al., 2019; Peng et al., 2019 ). Less is known about factors and mechanisms related to reading among diverse learners, a critical barrier to the field’s ability to address and prevent reading difficulty when it arises. Investigations with large and diverse participant samples are needed to improve understanding of how child characteristics additively and synergistically affect reading acquisition ( Hernandez, 2011 ; Lonigan et al., 2013 ). Insufficient research disentangles the influence of English-learner status for children who also have identified disabilities (Solari et al., 2014; Wagner et al., 2005 ). Greater attention to how language variation (e.g., dialect use) and differences in language experience affect reading development is crucial ( Patton Terry et al., 2010 ; Seidenberg & MacDonald, 2018; Washington et al., 2018). New realizations of the interaction between child characteristics and the depth of the orthography have also highlighted the importance of implicit learning in early reading ( Seidenberg, 2005 ; Steacy et al., 2019). Innovative cross-linguistic research is exploring how diverse methods of representing pronunciation and meaning within different orthographies, and children’s developing awareness of these methods, jointly predict reading skills (e.g., Kuo & Anderson, 2006 ; Wade-Woolley, 2016 ). Furthermore, a better understanding of the role of executive function, socio-emotional resilience factors, and biopsychosocial risk variables (e.g., poverty and trauma) on reading development is critical. Additional research like this, in English and across languages, is needed to develop effective instruction and assessments for all leaners.

A clearer understanding of child and contextual influences on the development of reading also will support improvements in how early and accurately children at risk for reading difficulties and disabilities are identified. Currently, numerous challenges remain in identifying children early enough to maximize benefits of interventions ( Colenbrander et al., 2018 ; Gersten et al., 2017b ). Investigators often use behavioral precursors or correlates of reading to estimate children’s risk for reading failure. Whereas this work has shown some promise ( Catts et al., 2015 ; Compton et al., 2006 , 2010 ; Lyytinen et al., 2015 ; Thompson et al., 2015 ), identification of risk typically involves high error rates, especially for preschoolers and kindergarteners who might benefit most from early identification and intervention. Similar challenges to accuracy have emerged when identifying older children with reading disabilities. Historically, this process has relied on discrepancy models (e.g., such as between reading skill and general cognitive aptitude), often yielding a just single comparison on which decisions are based (Waesche et al., 2011).

Challenges to identification for both younger and older children may be best met with frameworks that recognize the multifactorial casual basis of reading problems ( Pennington et al., 2012 ). Newer models of identification that combine across multiple indicators of risk derived from current skill, and that augment these indicators with other metrics of potential risk, may yield improved identification and interventions (e.g., Erbeli et al., 2018 ; Spencer et al., 2011). In particular, future research will need to consider and combine, while considering both additive and interactive effects, a wide array of measures, which may include genetic, neurological, and biopsychosocial indicators ( Wagner et al., 2019 ). Furthermore, more evaluation is needed of some new models of identification that integrate both risk and protective, or resiliency, factors, to see if these models increase the likelihood of correctly identifying those children most in need of additional instructional support (e.g., Catts & Petscher, 2020 ; Haft et al., 2016 ). Even if beneficial, it is likely that for early identification to be maximally effective, early risk assessments will need to be combined with progress monitoring of response to instruction ( Miciak & Fletcher, 2020 ). Of course, for such an approach to be successful, all children must receive high-quality reading instruction from the beginning and interventions need to be in place to address children who show varying levels of risk ( Foorman et al., 2016a ). Identifying children at risk and providing appropriate intervention early on has the potential to significantly improve reading outcomes and reduce the negative consequences of reading failure.

Intervention Innovations

Despite successes, too many children still struggle to read novel text with understanding, and intervention design efforts have not fully met this challenge ( Compton et al., 2014 ; Phillips et al., 2016 ; Vaughn et al., 2017 ). Greater creativity and integration of research from a broader array of complementary fields, including cognitive science and behavioral genetics may be required to deal with long-standing problems. For example, genetic information may have causal explanatory power; randomized trials are needed to evaluate the efficacy of using such information to select and individualize instruction and intervention ( Hart, 2016 ).

The field would benefit from increased attention to the problem of fading intervention effects over time. Although there can be detectable effects of interventions several years after they are completed (e.g., Blachman et al., 2014 ; Vadasy et al., 2011 ; Vadasy & Sanders, 2013 ), invariably effect sizes reduce over time. A meta-analysis of long-term effects of interventions for phonemic awareness, fluency, and reading comprehension found a 40 percent reduction in effect sizes within one year post-intervention ( Suggate, 2016 ). Perhaps reading interventions with larger initial effects or sequential reading interventions with smaller but cumulating effects would be more resistant to fade-out.

Solutions to the problem of diminishing effects may be inspired by examples from other fields. The field of memory includes examples of content that appears immune from forgetting. This phenomenon has been called permastore ( Bahrick, 1984 ). For example, people only meaningfully exposed to a foreign language in school classes will still retain some knowledge of the language 50 years later. Additionally, expertise in the form of world-class performance appears to result from cumulative effects of long-term deliberate practice ( Ericsson, 1996 ), and skilled reading can be viewed as an example of expert performance ( Wagner & Stanovich, 1996 ). Informed by these concepts and by advances in early math instruction (e.g., Sarama et al., 2012 ; Kang et al., 2019 ), reading intervention studies should prioritize follow-up evaluations, including direct comparisons of follow-through strategies aimed at sustaining benefits from earlier instruction. For example, studies should evaluate booster interventions, professional development that better aligns cross-grade instruction, and how re-teaching and cumulative review may consolidate skill acquisition across time (e.g., Cepeda et al., 2006 ; Smolen et al., 2016 ).

Translational and Implementation Science

If the science of reading is to be applied in a manner resulting in achievement for all learners, the field must increase its focus on processes supporting implementation of evidence-based reading practices in schools. The field can leverage its considerable evidence-base to systematically investigate, with replication, both the effectiveness of reading instructional practices with diverse learners and to investigate processes that facilitate or prevent adoption, implementation, and sustainability of these practices (National Research Council, 2002; Schneider, 2018 ; Slavin, 2002 ). Research on these processes in educational contexts may be best facilitated by making use of methodological and conceptual tools developed within the traditions of translation and implementation science research ( Gilliland et al., 2019 ; Eccles & Mittman, 2006 ). For example, these frameworks can support studies on whether and how educators and policymakers use information about evidence to inform decision making (e.g., Farley-Ripple et al., 2018 ) and studies on how institutional routines may need to be adapted to best integrate new procedures and practices (e.g., scheduling changes in the school day; Foorman et al., 2016b ).

Reading research that uses translational and implementation science frameworks and methodologies will make more explicit the processes of adoption, implementation and sustainability and how these interact within diverse settings and with multiple populations ( Brown et al., 2017 ; Fixsen et al., 2005 , 2013 ). This work will be guided by new questions, not only asking “what works” but also “what works for whom under what conditions” and “what factors promote sustainability of implementation.” Innovative studies would adhere to rigorous scientific standards, prioritize hypothesis testing within a deductive, experimental framework, and leverage qualitative methodologies to systematically explore implementation processes and factors ( Brown et al., 2017 ). Results could iteratively inform the breadth of scientific reading research, including basic mechanisms related to reading and the development of novel assessments and interventions to support achievement among diverse learners in diverse settings ( Cook & Odom, 2013 ; Douglas et al., 2015 ; Forman et al., 2013 ).

There has recently been a resurgence of the debate on the science of reading, and in this article, we described the existing evidence base and possible future directions. Compelling evidence is available to guide understanding of how reading develops and identify proven instructional practices that impact both decoding and linguistic comprehension. Whereas there is some evidence that is either not compelling or has yet to be generated for instructional practices and programs that are widely used, the scientific literature on reading is ever-expanding through contributions from the fields education, psychology, linguistics, communication science, neuroscience, and computational sciences. As these additions to the literature mature and contribute to an evidence base, we anticipate they will inform and shape the science of reading as well as the science of teaching reading.

Acknowledgments

First author was determined by group consensus. Authors equally contributed and are listed and alphabetically. The authors’ work was supported by funding from the Chan Zuckerberg Initiative, the Institute of Education Sciences (R305A160241, R305A170430, R305F100005, R305F100027, R324A180020, R324B19002) and Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50HD52120, P20HD091013, HD095193, HD072286).

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How to Read Research Papers— Unveiling AI Tool for Reading

Table of Contents

Reading research papers is an essential skill for students, academics, and professionals in various fields. It allows you to stay updated with the latest findings, develop critical thinking skills, and contribute to scholarly discussions. However, understanding these papers can be challenging due to their complex language and structure. That’s why we have written this article, which will provide you with comprehensive strategies on how to read a research paper effectively.

Let’s get started with how to identify the structure of a research paper!

Identify the structure of a research paper

Understanding the structure of a research paper is the first step toward how to read research paper effectively. Most research papers follow a standard structure, which includes an abstract , introduction , methodology , results, discussion and conclusion . Familiarizing yourself with the research paper structure can help you navigate the paper and understand its content.

Each section of a research paper serves a specific purpose. The abstract provides a summary of the entire research paper, the introduction presents the research question, the methodology explains how the research was conducted, the results section presents the findings, the discussion interprets these findings, and the conclusion summarizes the paper and suggests areas for future research.

Source: University of Wisconsin

Abstract: The abstract serves as a concise summary of the entire research paper. To efficiently grasp its content, focus on key elements such as the research question, methodology, and significant findings. This will provide a quick overview and help you decide whether the paper aligns with your interests.

Introduction: The research paper introduction sets the stage for the research, presenting the problem statement and the purpose of the study. Take note of the research gap, hypotheses, and objectives discussed here to understand the context of the paper.

Methodology: Understanding the methods employed in a study is crucial for evaluating the research's validity. Take note of the research design, data collection, and analysis methods to comprehend how the study was conducted.

Results: The results section presents the outcomes of the research. Approach this section with a critical mindset, assessing whether the results align with the research question and the methods used. Consider the implications of the findings within the broader context of the field.

Conclusion: The conclusion summarizes the key findings and their significance. It's a crucial part of the paper that brings together the entire study. Take the time to reflect on how the research contributes to the existing body of knowledge.

Citations: Follow the trail of references provided in the paper. This not only enhances your understanding but also leads you to related works that can deepen your knowledge of the subject.

More tips on how to read research papers effectively

Developing effective reading strategies can help you understand research papers more efficiently. These strategies include active reading, note-taking, and using AI tools for summarizing and understanding research papers.

Active reading involves engaging with the text, asking questions, and making connections. Note-taking helps you remember important information and organize your thoughts. Summarizing using AI tools allows you to condense the information and understand the main points of the paper easily.

Active Reading:

Active reading is a strategy that involves interacting with the text. This can include highlighting important information, making notes in the margins, and asking questions. Active reading can help you understand the content of the paper and remember it more effectively.

When reading a research paper, try to identify the main points, arguments, and evidence. Ask yourself questions like:

• What is the research question?
• What methods were used to answer it?
• What were the results? What conclusions were drawn?

This will help you engage with the paper and understand its content.

Source: https://idaho.pressbooks.pub/write/chapter/reading-for-writing/

Note-Taking:

Note-taking is another effective reading strategy. It involves writing down important information, ideas, and questions. Note-taking can help you remember the content of the paper, organize your thoughts, and prepare for discussions or writing assignments.

When taking notes, try to be concise and use your own words. This will help you understand the information and remember it more effectively. You can also use symbols or diagrams to represent complex ideas.

Source: University of Toronto

Using AI Tools to Summarize Research Paper:

When research papers are flooded with complex language, jargon, and acronyms, it’s important to use AI summarizer that helps you breakdown the sentences and makes it easier to read the information. In that case, you can make use of SciSpace Copilot which not only explains the highlighted section or paragraph, but also explains you the equations, tables, figures, and images present in the research paper. You can also rely on other AI tools to comprehend research papers in a short span of time.

Watch this video to learn how to use the AI summarizer:

Dealing with Technical Jargon:

Research papers often contain a lot of technical jargon. Don't be intimidated; instead, create a glossary for yourself. Look up unfamiliar terms and gradually build your understanding of the terminology used in your field of interest. As mentioned above, you can use AI summarizer to decode the jargon and get the essence of the research paper.

Joining Academic Communities:

Engage in discussions and forums related to your area of interest. Academic communities provide valuable insights, differing perspectives, and opportunities for networking with experts in the field.

Staying Updated on Research Trends:

To read research papers effectively, it's crucial to stay informed about the latest developments in your field. Subscribe to academic journals, follow reputable researchers on social media, and attend conferences or webinars to stay updated.

Using Academic Search Engines:

Make use of online tools and databases such as Google Scholar, PubMed, SciSpace , and academic journals to access a vast repository of research papers. These platforms often provide additional features like citation tracking and related articles, enriching your reading experience.

Also Read: Beast Academic Search Engines(2024)

Reading research papers is a complex task that requires a good understanding of the structure of a research paper, effective reading strategies, and the ability to interpret results. However, with practice and patience, you can develop these skills and become proficient at reading research papers.

Remember, the goal is not just to read the paper, but to understand it, evaluate it, and use it to contribute to your own research or professional development.

Frequently Asked Questions

Active reading helps understand research papers better. It involves activities like highlighting, taking notes, asking questions, and summarizing. This makes it easier to understand and evaluate the research material.

Taking notes during research helps you remember important information, stay organized, avoid plagiarism, think critically, and serve as a reference for future use, allowing you to revisit key points and findings as needed.

SciSpace notebook is the go-to tool for taking notes effortlessly

The best AI tool for reading research papers varies based on individual needs. A popular AI tools include SciSpace Copilot.

Using AI tools to read research papers is easy. First, choose a tool, example — SciSpace Copilot. Then, upload your paper. It analyzes it and explains it in a language of your choice. You can then use this summary to help with your research or understanding of the topic.

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On reading research papers

We’ll be reading a lot of research papers in this course, so over the semester you will naturally develop your own way to read a research paper. Use these guides to get started.

First, some basic points; then, concrete reading guides.

A research paper encapsulates enormous effort

A good research paper distills significant work by its authors. My group has worked for years on tens of thousands of lines of code and huge numbers of experiments, most of which got thrown away, to produce a single 12-page paper. A paper’s authors are trying to boil down everything they learned into something you can digest. A single sentence may represent a full year of misdirected effort.

Of course, there are many kinds of effort, and a great research paper may represent a flash of insight rather than toil. That insight still required real work, namely everything the researcher did to prepare themselves to receive it.

A research paper encapsulates a moment in history

Any research paper is a picture of its time. The paper was written in a context shaped by technology and society. What hardware was available? What kinds of research were exciting to the community at the time? What kinds of research were being funded? An open reading can teach you a lot about what people were thinking in the months and years before publication.

A research paper deserves critical attention

As of 2019, more than 7 million scientific papers are published per year . They are not all equally good; some are outright fraudulent. We will try to avoid the really bad ones, but you will still find that all research papers have weaknesses, and for some papers the weaknesses may overwhelm the strengths. Some papers fail on their own terms when read carefully; some will fail to interest you because of your own cast of mind. Nevertheless, you can and should learn something from each paper.

You owe a research paper nothing

When you read a paper, your goal is extractive : What can this paper teach you , now ? A paper is not a precious artwork demanding a respectful, hushed approach. Skim it, skip around in it, disagree with it, rip it apart—whatever it takes to learn what you can—and when you’ve learned what you can, drop it. Despite the effort and history that formed the paper, you owe the paper nothing.

I read best when I read with curiosity, openness, and skepticism. The skepticism keeps me curious: What’s really going on in these experiments? The openness keeps me interested: even if I’m not interested in the topic, maybe there’s some trick I could learn from; and maybe the paper will show me why I should care about the topic after all.

Concrete reading guides

These guides have concrete advice on the reading process. Keshav’s is especially well known in the systems community.

• S. Keshav’s “How to Read a Paper”
• Michael Mitzenmacher’s “How to Read a Research Paper”
• Jennifer Raff’s “How to Read and Understand a Scientific Article”

These guides are great. They also contradict. (Keshav says to read the abstract first; Raff says to never read the abstract until the end.) There’s no one right way to read a paper. The literatures in different sciences have different qualities (for example, unfortunately for you, computer systems papers tend to be verbose), and our minds are different. We also read for different goals. Reading a paper in order to review it requires more antagonism than reading a long-published, well-cited work. And particularly at the beginning of this course, when we are reading multiple historical papers per course meeting rather than one current paper, I expect you to spend less than “three to four hours” per paper!

Public reading groups

You may be interested in these public examples of reading research papers.

• Adrian Colyer’s “The Morning Paper” blog (on hiatus, but great archives)
• Papers We Love

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May 9th, 2016

How to read and understand a scientific paper: a guide for non-scientists.

94 comments | 1974 shares

Estimated reading time: 7 minutes

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My post,  The truth about vaccinations: Your physician knows more than the University of Google  sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that their paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection, outbreaks happen .

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field. And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a  basic understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice

Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g. the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven. Tip: g oogle “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by Pubmed . [EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out Web of Science for a more complete index of science journals. And please feel free to share other resources in the comments!]  Beware of questionable journals .

As you read, write down every single word that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the only part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract last. I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain why this research has been done in order to understand it.

4. Identify the SPECIFIC QUESTION(S)

What exactly are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read this , then go back to my last post and read one of the papers that I linked to (like this one ) and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean literally draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

Image credit: author

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7. Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results mean , just write down what they are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but here , here , and here are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

Things to pay attention to in the results section:

• Any time the words “significant” or “non-significant” are used. These have precise statistical meanings. Read more about this here .
• If there are graphs, do they have error bars on them? For certain types of studies, a lack of confidence intervals is a major red flag.
• The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors think the results mean? Do you agree with them? Can you come up with any alternative way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP: (Don’t neglect doing this) What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

UPDATE: If you would like to see an example of how to read a science paper using this framework, you can find one here .

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

I’ve written a shorter version of this guide for teachers to hand out to their classes. If you’d like a PDF, shoot me an email: jenniferraff (at) utexas (dot) edu. For further comments and additional questions on this guide, please see the Comments Section on the original post .

This piece originally appeared on the author’s personal blog and is reposted with permission.

Featured image credit:  Scientists in a laboratory of the University of La Rioja  by Urcomunicacion  (Wikimedia CC BY3.0)

Note: This article gives the views of the authors, and not the position of the LSE Impact blog, nor of the London School of Economics. Please review our  Comments Policy  if you have any concerns on posting a comment below.

About the Author

Jennifer Raff (Indiana University—dual Ph.D. in genetics and bioanthropology) is an assistant professor in the Department of Anthropology, University of Kansas, director and Principal Investigator of the KU Laboratory of Human Population Genomics, and assistant director of KU’s Laboratory of Biological Anthropology. She is also a research affiliate with the University of Texas anthropological genetics laboratory. She is keenly interested in public outreach and scientific literacy, writing about topics in science and pseudoscience for her blog ( violentmetaphors.com ), the Huffington Post , and for the Social Evolution Forum .

About the author

94 Comments

Very good Indeed.I always Read Abstract First Time always ……Thanks

Great information and guide to reading and understanding scientific paper. However, there are non-scientific student asked to do scientific research and it would be great to actually give an example and you point out the answers to the steps in the sample article or journal cited. Thank you.

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I can summarize it eve further: three stars by a number in a table = good, no stars = bad

within the context of the fact that a very sizable portion of scientific papers are falsified, what does this article mean?

Your “fact” needs explanation and evidence, otherwise it can be considered alternative.

That’s why you don’t skip step 11

I think it would be useful also to point out that, even after diligently pursuing all of these excellent steps, the reader is usually still unable to determine whether the subjects or materials even existed. Unlike with lay media, where most important stories are covered by multiple sources, and where facts are sometimes checkable from primary sources – even by readers – it is rare indeed that a reader can go beyond the words on the page.

Is the fact that you read instructions on how to read a paper not evidence that there is something wrong with the way we write papers?

The issue of scientific literacy is always challenging for my students. But this is the most practical and helpful guide I’ve ever seen on the web, thanks for this. I usually share with my students the following tips already mentioned above: – Learn the vocabulary before reading – Summarize the background in five sentences or less – Identify the BIG QUESTION

But the pieces of advice this guide gives are structured better and easier. I especially love this one: Don’t yet try to decide what the results mean, just write down what they are. Thanks again for writing this piece!

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you left out ask for the data, so you can check for yourself… (ie trust but verify)

an example a psychology paper that surveyed a group of people about conspiracy theories (n=137) and it’s main/only novel finding was that people that believed in conspiracies theories, there was a tendency for people to believe in mutually contradictory conspiracy theories. ie individual could believe that Princess Diana faked her own death, whilst at the same time had been murdered by MI5

The paper, was duly called – Dead and Alive – M Wood et al…

However. after requesting the data. there was not a single individual person that ticked the survey boxes, that simultaneously believed this finding. Not one person.

The problem, most people surveyed did not believe either of those conspiracies, and inappropriate stats method was applied to data, that assumed a non skewed dataset. Thus, not believing in A and not believing in B correlated, but it also gave a ‘result that believing in A, and Believing in B also correlated..

A very dumb paper… Author still hasn’t retracted it yet.

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I love this! Great simmered-down resource for my undergrads- both science and non-science majors. Thanks for sharing!

“Web of Science” link is broken (at least for me) but a useable alternative is webofknowledge.com (same resource, different name).

I think it is important to note that the journal in which a paper is published is no proof as to the rigor of that paper. A listing in PubMed does not guarantee quality; thus, you need to focus on teaching people how to interpret the paper without relying on a simple JTASS approach to initial assessment. This may be a guide, but nothing more. I say this as a former editor of a MEDLINE journal. There can be good papers in bad journals and bad papers in good ones. But you are correct. Key questions are: What is the question? How will we answer the question? What answer did we get? Did we use the right tools to answer the question? What do we think it means? What else could we do? And thus we can train people to watch for sleights of hand, such as shifting primary outcomes, data mining, salami slicing, etc.

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Yikes! This is a lot of work just to read a single paper! It’s almost the same as writing a paper! I understand the logic in why you recommend this, but the average person is going to be willing to spend 20-30 minutes reading and trying to learn. This method calls for multiple hours of effort and I just don’t seem many non-scientist people being willing to do that when they’re more curious than actually invested. I was really hoping this entry was going to make it easier to navigate the foreign and confusing world that these papers represent, and it probably will if someone does this process repeatedly for quite some time…..like a scientist…..but most of us aren’t scientists and don’t have that kind of time to dedicate to something that’s not our work or family.

By tradition, we expect our scientists to report their findings by codifying them in unreadable gobbledygook. Then we write instructions on how to decode that unreadable nonsense!!

We need to encourage papers to be written in everyday language so it is easier for all. Problem solved.

I wholeheartedly agree with Kaveh Bazargan. From personal experience as a non-scientist trying to do this with medical research papers is a very intimidating and isolating experience. Most people don’t have the time spare to even try to learn this skill. It would be great if systematic reviewers who are acknowledged experts in reading and analysing papers could find a way of communicating the important information about individual papers to non-scientists before – or instead of – burying them in systematic reviews and meta-analyses which are even more difficult to understand. Structured plain language summaries of primary research would be very helpful rather than individuals having to teach themselves how to read and understand a scientific paper which is written for other scientists in “unreadable goggledygook”. Many (most?) papers conceal methodogical flaws in the research conduct which are almost impossible to spot without years of scientific training.

I love this! Extraordinary cooled off assets for my students both science and non-science majors. A debt of gratitude is in order for sharing!

Regarding step 11, if you have access to Web of Science I recommend looking up how many citations the paper has (this will also vary depending on the age of the paper) and who cites it, and whether there even any replies to it in the peer-reviewed literature.

Do you literally do this for every paper you read? I’m curious how much time it takes you to go from start to finish on what you would consider a typical paper. How often do you read new articles a week?

This post has the laudable goal of helping nonscientists understand the primary literature, but the recommendations seem even more onerous than they have to be. For example, the idea that one should write down every single word that he/she doesn’t know? That sounds more like a task for a scientist scrutinizing the work of a rival. For a nonscientist, there may be dozens and dozens of unknown words, and chasing down the meaning of each one may cause a serious forest/trees problem. I agree that there’s no substitute for the hard work of digging into a paper, but following the prescribed advice to the letter would be utterly exhausting for almost any lay reader. I base these comments on my experiences as a biology researcher and undergraduate instructor.

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I really like your post and the effort, but much of the problem wouldn’t exist if we, academics, did a better job in writing down the correct conclusions. Researcher degrees of freedom are seldom properly understood and we keep on having the tendency to be overdeterministic about statistics that are not intended as such. Of course we want to communicate in black and white about our tests (significance!) because it is a human tendency to persuade the reader. Most of the research probably is not as inconsistent as it first seems but we forget to report the proper statistics to see so (CI around the ES)

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Thank you very much for sharing a guide that will help me to follow the best standards for writing a scientific paper even I am not a scientist.

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Reading the abstract last is one, not the, way to read a paper. It it biases the naive reader, then they are not reviewing with a level of skepticism required to evaluate science. We put abstracts first because they lay out the problem, overview the sample and design, and tersely describe what they think they discovered. Then, as I read, I have a roadmap in my head of what to look for to determine for myself whether or not they found something noteworthy.

What is the problem? Are hypotheses to be tested likely to illuminate/clarify the problem? Is the sample appropriate for testing and was it sampled without imputing bias? Were measures appropriate and do they have a history of validity? We the analytics applied appropriate for testing at the level of power needed give the sample size? [Here even many scientist are ill-equipped to judge.] After enumerating results, do the authors list weaknesses in their design that might suggest replication is necessary? If not, check for snow – as in snowjob. If significance levelsare low or variables correlate with one another too much, are moderators discussed? [e.g., results hold for males but not females, old vs young, fat vs skinny, etc.). If so, why were data not re-analyzed to control for moderator effects on results?

Lastly, if the word “prove” appears anywhere in the paper, assume it is junk science (like fake news). Research is never ever done to prove anything. Research is only done to find out. Once a preponderance of studies report a similar finding looking at the same problem with different people, measures, designs, and statistical analyses, then you have something like proof; consensus.

Lastly, if you are a conspiracy theory believer, you will disbelieve any scientific study that does not support your word view. Keep this in mind. A few studies that run counter to the prevailing consensus is not PROOF that your conspiracy is correct, and mainstream science is wrong. I do not know a single scientist (and I know thousands globally) who do not consider climate change to be well-evidenced. Similarly, evolutionary theory remains useful – our current understanding of genomic medicine hinges on cellular mutation, which is evolution on a microscopic scale.

This is a very useful set of instructions, but I found the following statement highly amusing: “Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g. the Discovery Institute) may appear to be legitimate research institutions but are actually agenda-driven.”

All research institutions are agenda driven (including my alma mater, the University of Texas), because funding and professional advancement depend on results. Researchers are fallible humans and subject to temptation and error. There is a very big lawsuit pending against Duke University (see below) for falsifying data.

When I read any research (especially medical), I now search for evidence of legal or professional action. So you might add that as #12: “Lawsuits? Retractions?” Caveat lector.

http://science.sciencemag.org/content/353/6303/977.full

http://www.dukechronicle.com/article/2016/09/experts-address-research-fabrication-lawsuit-against-duke-note-litigation-could-be-protracted

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Weird advice, like: ‘I always read the abstract last’ . This is advice for referees, not for general readers. I always read the abstract first.

An abstract can be misleading, but I am often not qualified enough to judge that. Actually, this blog post title and abstract are misleading too: your advice is for referees, not for non-scientists. So you wanted to provide an immersive experience into a misleading piece, well done 😉

First thing, get rid of the word proof. This is a huge error in that even if you have reputable scientists, journals, institutions, etc. that what is published, especially in a single article, is anything resembling a fact. It is merely research findings from one instance and in no way forms a fact. This is the next level of misinterpretation of science, even among those able to comprehend the journal article, that science produces or discovers facts. There is nothing that is factual that we know of.

Several comments:

For the mid-term exam in a graduate class I took in experimental design the professor would select half a dozen articles from the peer reviewed literature, tell her students to pick three and explain what they had done wrong. New articles for every class and she never ran out.

Beware of articles published in inappropriate journals, no matter how respectable (E.g., something about sociology or criminology published in a medical journal). This is a strategy for sneaking agenda driven research past the peer review process by going to a journal whose reviewers are likely to be unfamiliar with the subject while the editors are sympathetic to the agenda.

There is a reason research papers are written in what looks like “scientific gobbledygook” to lay persons. They are not intended for a lay audience and the goal is to be extremely precise with the technical details of what was done and found so other scientists can examine the results and, most important, attempt to replicate them.. There is no way to simplify the language and put it in lay terms without losing the precision required for a scientific study. E.g., a particle physicist may give a lay explanation of an experiment in metaphorical terms of little balls of energy smashing into each other, but their peers are going to want to see the pages and pages of mathematics that really describe what was happening.

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I would add “Check the source of funding for the research.” If paper on the safety of glyphosate is funded by Bayer or Monsanto, or a paper on climactic change is funded by Exxon, read no further.

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Get the dissertation writing service students look for these days with the prime focus being creating a well researched and lively content on any topic.

The non-scientist should pay extra attention towards this article for the non-technical writing and understanding for them.

A lot of a researcher’s work includes perusing research papers, regardless of whether it’s to remain progressive in their field, propel their logical comprehension, survey compositions, or assemble data for a task proposition or concede application. Since logical articles are not the same as different writings, similar to books or daily paper stories, they ought to be perused in an unexpected way.

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Thanks, I’ll use this a lot for my MSc Thesis.

Those are some great tips but please don’t forget that each school has its own requirements to academic papers.

Clarifying your methodology for reading science paper: excellent idea and great information. Thanks a lot!

Thanks for sharing this blog. Its very helpful for me and I bookmarked this for future

Excelente trabajo, original. Lo recomendaré para mis estudiantes de Posgrado. Si no hay problema, me gustaría hacer una traducción al castellano para el uso de mis estudiantes de pregrado de Sociología.

Excellent work,original. I will recommend it for my graduate students. If there is no problem, I would like to make a translation into Spanish for the use of my undergraduate Sociology students.

Hi Luis, all our works are CC licensed so you are more than welcome to make a translation provided you link back to the original source. See here for details: https://creativecommons.org/licenses/by/3.0/deed.en_GB

Great information , it is very helpful thanks for sharing the blog .

Step 1 and 10 is a great idea, but I still think it’s possible to read the abstract with the introduction and still keep an open mind? and shouldn’t they keep their results for the interpretation section? sorry new to reading scientific papers

Step 1 and 10 is a great idea, but I still think it’s possible to read the abstract with the introduction and still keep an open mind? and shouldn’t they keep their results for the interpretation section? sorry new to reading scientific papers

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Thank you for sharing the tips, they were very helpful.

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The article is extremely helpful. Considering that scientific research are not as easy, the tips in the article are great.

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Thank you for posting this. It has really helped a lot, especially for those of us who always read the abstract first haha

Thanks for writing this blog. It is very much informative and at the same time useful for me

Yeah, great advice on how to be objective from someone who openly declares their prejudice in the opening statement.

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Do you in a real sense do this for each paper you read? I’m interested what amount of time it requires for you to go beginning to end on what you would think about an average paper. How frequently do you read new articles seven days?

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That is literally my question too, I see it as quite time consuming to conduct such a lengthy process for all scientific articles we come across especially as one has other responsibilities to give attention too

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There is a reason research papers are written in what looks like “scientific gobbledygook” to lay persons. They are not intended for a lay audience and the goal is to be extremely precise with the technical details of what was done and found so other scientists can examine the results and, most important, attempt o replicate them.

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Thanks for posting this. You are doing a service to the general public and also graduate students by not only posting this but answering all sincere questions. I have a Ph. D. in Zoology and have been a peer-reviewer for at least 12 papers and am first author of three peer-reviewed papers. I have taught statistics in two universities as a contract professor and all of my papers rely on use of statistics. To answer a frequently asked question, yes, personally it can take me a couple of hours or several more to read some papers. This is true for my colleagues as well. Scientific papers are written so as to be as concise as possible and this can make them hard to read. They often also use technical terms which one has to look up. At least biology and statistics. nothing I have read (or written) has been in “goobledygook” or purposely incomprehensible jargon but they do use terms and concepts that are probably unfamiliar to the layman. I think what the author means, by her comment on absstracts can be intepreted as “don’t JUST read the abstract. Be sure to read the introduction. Personally I go to the discussion and conclusion next.

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Your writing skills and passion for sharing your knowledge and experiences are truly outstanding. . Keep writing and inspiring others with your words.

I would add, look at who funded the study and their financial interests. Most science is not independent it is funded by those with an agenda. Look at the demographic data, length of time the study took place, what was left out, where you might need more information. Look at who was included and excluded in the data set. Anyone that has taken statistics knows what you include or exclude in the data set can skew and or outright change the outcome.

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How to Read Research Papers: A Cheat Sheet for Graduate Students

• August 4, 2022
• PRODUCTIVITY

It is crucial to stay on top of the scientific literature in your field of interest. This will help you shape and guide your experimental plans and keep you informed about what your competitors are working on.

To get the most out of your literature reading time, you need to learn how to read scientific papers efficiently. The problem is that we simply don’t have enough time to read new scientific papers in our results-driven world. 

It takes a great deal of time for researchers to learn how to read research papers. Unfortunately, this skill is rarely taught.

I wasted a lot of time reading unnecessary papers in the past since I didn’t have an appropriate workflow to follow. In particular, I needed a way to determine if a paper would interest me before I read it from start to finish.

So, what’s the solution?

This is where I came across the Three-pass method for reading research papers. 

Here’s what I’ve learned from using the three pass methods and what tweaks I’ve made to my workflow to make it more personalized.

Build time into your schedule 

Before you read anything, you should set aside a set amount of time to read research papers. It will be very hard to read research papers if you do not have a schedule because you will only try to read them for a week or two, and then you will feel frustrated. An organized schedule reduces procrastination significantly.

 For example, I take 30-40 minutes each weekday morning to read a research paper I come across.

After you have determined a time “only” to read research papers, you have to have a proper workflow.

Develop a workflow

For example, I follow a customized version of the popular workflow, the “Three-pass method”. 

When you are beginning, you may follow the method exactly as described, but as you get more experienced, you can make some changes down the road.

Why you shouldn’t read the entire paper at once?

Oftentimes, the papers you think are so important and that you should read every single word are actually worth only 10 minutes of your time.

Unlike reading an article about science in a blog or newspaper, reading research papers is an entirely different experience. In addition to reading the sections in a different order, you must take notes, read them several times, and probably look up other papers for details. 

It may take you a long time to read one paper at first. But that’s okay because you are investing yourself in the process.

However, you’re wasting your time if you don’t have a proper workflow. 

Oftentimes, reading a whole paper might not be necessary to get the specific information you need.

The Three-pass concept

The key idea is to read the paper in up to three passes rather than starting at the beginning and plowing through it. With each pass, you accomplish specific goals and build upon the previous one.

The first pass gives you a general idea of the paper. A second pass will allow you to understand the content of the paper, but not its details. A third pass helps you understand the paper more deeply.

The first pass (Maximum: 10 minutes)

The paper is scanned quickly in the first pass to get an overview. Also, you can decide if any more passes are needed. It should take about five to ten minutes to complete this pass.

Carefully read the title, abstract, and introduction

You should be able to tell from the title what the paper is about. In addition, it is a good idea to look at the authors and their affiliations, which may be valuable for various reasons, such as future reference, employment, guidance, and determining the reliability of the research.

The abstract should provide a high-level overview of the paper. You may ask, What are the main goals of the author(s) and what are the high-level results? There are usually some clues in the abstract about the paper’s purpose. You can think of the abstract as a marketing piece.

As you read the introduction, make sure you only focus on the topic sentences, and you can loosely focus on the other content.

What is a topic sentence?

Topic sentences introduce a paragraph by introducing the one topic that will be the focus of that paragraph. 

The structure of a paragraph should match the organization of a paper. At the paragraph level, the topic sentence gives the paper’s main idea, just as the thesis statement does at the essay level. After that, the rest of the paragraph supports the topic.

In the beginning, I read the whole paragraph, and it took me more than 30 minutes to complete the first pass. By identifying topic sentences, I have revolutionized my reading game, as I am now only reading the summary of the paragraph, saving me a lot of time during the second and third passes.

Read the section and sub-section headings, but ignore everything else 

Regarding methods and discussions, do not attempt to read even topic sentences because you are trying to decide whether this article is useful to you.

Reading the headings and subheadings is the best practice. It allows you to get a feel for the paper without taking up a lot of time.

Read the conclusions

It is standard for good writers to present the foundations of their experiment at the beginning and summarize their findings at the end of their paper.

Therefore, you are well prepared to read and understand the conclusion after reading the abstract and introduction.

Many people overlook the importance of the first pass. In adopting the three-pass method into my workflow, I realized that many papers that I thought had high relevance did not require me to spend more time reading. 

Therefore, after the first pass, I can decide not to read it further, saving me a lot of time.

Glance over the references

You can mentally check off the ones you’ve already read.

As you read through the references, you will better understand what has been studied previously in the field of research.

First pass objectives

At the end of the first pass, you should be able to answer these questions: 

• What is the  category  of this paper? Is it an analytical paper? Is it only an “introductory” paper? (if this is the case, probably, you might not want to read further, but it depends on the information you are after)or is it an argumentative research paper?
• Does the  context  of the paper serve the purpose for what you are looking for? If not, this paper might not be worth passing on to the second stage of this method.
• Does the basic logic of the paper seem to be valid? How do you comment on the  correctness  of the paper?
• What is the main  output  of the paper, or is there output at all?
• Is the paper well written? How do you comment on the  clarity  of the paper?

After the first pass, you should have a good idea whether you want to continue reading the research paper.

Maybe the paper doesn’t interest you, you don’t understand the area enough, or the authors make an incorrect assumption. 

In the first pass, you should be able to identify papers that are not related to your area of research but may be useful someday. 

You can store your paper with relevant tags in your reference manager, as discussed in the previous blog post in the  Bulletproof Literature Management System  series.

This is the third post of the four-part blog series:  The Bulletproof Literature Management System . Follow the links below to read the other posts in the series:

• How to How to find Research Papers
• How to Manage Research Papers
• How to Read Research Papers (You are here)
• How to Organize Research Papers

The second pass (Maximum: 60 minutes)

You are now ready to make a second pass through the paper if you decide it is worth reading more.

You should now begin taking some high-level notes because there will be words and ideas that are unfamiliar to you. 

Most reference managers come with an in-built PDF reader. In this case, taking notes and highlighting notes in the built-in pdf reader is the best practice. This method will prevent you from losing your notes and allow you to revise them easily.

Don’t be discouraged by everything that does not make sense. You can just mark it and move on. It is recommended that you only spend about an hour working on the paper in the second pass. 

In the second pass:

• Start with the abstract, skim through the introduction, and give the methods section a thorough look. 
• Make sure you pay close attention to the figures, diagrams, and other illustrations on the paper. By just looking at the captions of the figures and tables in a well-written paper, you can grasp 90 percent of the information. 
• It is important to pay attention to the overall methodology . There is a lot of detail in the methods section. At this point, you do not need to examine every part. 
• Read the results and discussion sections to better understand the key findings.
• Make sure you mark the relevant references in the paper so you can find them later.

Objectives of the second pass

You should be able to understand the paper’s content. Sometimes, it may be okay if you cannot comprehend some details. However, you should now be able to see the main idea of the paper. Otherwise, it might be better to rest and go through the second pass without entering the third. 

This is a good time to summarize the paper. During your reading, make sure to make notes.

After the second pass, you can: 

• Return to the paper later(If you did not understand the basic idea of the paper)
• Move onto the thirst pass.

The third pass (Maximum: four hours)

You should go to the third stage (the third pass) for a complete understanding of the paper. It may take you a few hours this time to read the paper. However, you may want to avoid reading a single paper for longer than four hours, even at the third pass.

A great deal of attention to detail is required for this pass. Every statement should be challenged, and every assumption should be identified.

By the third pass, you will be able to summarize the paper so that not only do you understand the content, but you can also comment on limitations and potential future developments.

Color coding when reading research papers

Highlighting is one way I help myself learn the material when I read research papers. It is especially helpful to highlight an article when you return to it later. 

Therefore, I use different colors for different segments. To manage my references, I use Zotero. There is an inbuilt PDF reader in Zotero. I use the highlighting colors offered by this software. The most important thing is the concept or phrase I want to color code, not the color itself.

Here is my color coding system.

• Problem statement: Violet
• Questions to ask: Red (I highlight in red where I want additional questions to be asked or if I am unfamiliar with the concept)
• Conclusions: Green (in the discussion section, authors draw conclusions based on their data. I prefer to highlight these in the discussion section rather than in the conclusion section since I can easily locate the evidence there)
• Keywords: Blue
• General highlights and notes: Yellow

Minimize distractions

Even though I’m not a morning person, I forced myself to read papers in the morning just to get rid of distractions. In order to follow through with this process (at least when you are starting out), you must have minimum to no distractions because research papers contain a great deal of highly packed information.

It doesn’t mean you can’t have fun doing it, though. Make a cup of coffee and enjoy reading!

Images courtesy : Online working vector created by storyset – www.freepik.com

Aruna Kumarasiri

Founder at Proactive Grad, Materials Engineer, Researcher, and turned author. In 2019, he started his professional carrier as a materials engineer with the continuation of his research studies. His exposure to both academic and industrial worlds has provided many opportunities for him to give back to young professionals.

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Open Access

Ten simple rules for reading a scientific paper

* E-mail: [email protected]

Affiliation Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America

• Maureen A. Carey, 
• Kevin L. Steiner, 
• William A. Petri Jr

Published: July 30, 2020

• https://doi.org/10.1371/journal.pcbi.1008032
• Reader Comments

Citation: Carey MA, Steiner KL, Petri WA Jr (2020) Ten simple rules for reading a scientific paper. PLoS Comput Biol 16(7): e1008032. https://doi.org/10.1371/journal.pcbi.1008032

Editor: Scott Markel, Dassault Systemes BIOVIA, UNITED STATES

Copyright: © 2020 Carey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: MAC was supported by the PhRMA Foundation's Postdoctoral Fellowship in Translational Medicine and Therapeutics and the University of Virginia's Engineering-in-Medicine seed grant, and KLS was supported by the NIH T32 Global Biothreats Training Program at the University of Virginia (AI055432). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

“There is no problem that a library card can't solve” according to author Eleanor Brown [ 1 ]. This advice is sound, probably for both life and science, but even the best tool (like the library) is most effective when accompanied by instructions and a basic understanding of how and when to use it.

For many budding scientists, the first day in a new lab setting often involves a stack of papers, an email full of links to pertinent articles, or some promise of a richer understanding so long as one reads enough of the scientific literature. However, the purpose and approach to reading a scientific article is unlike that of reading a news story, novel, or even a textbook and can initially seem unapproachable. Having good habits for reading scientific literature is key to setting oneself up for success, identifying new research questions, and filling in the gaps in one’s current understanding; developing these good habits is the first crucial step.

Advice typically centers around two main tips: read actively and read often. However, active reading, or reading with an intent to understand, is both a learned skill and a level of effort. Although there is no one best way to do this, we present 10 simple rules, relevant to novices and seasoned scientists alike, to teach our strategy for active reading based on our experience as readers and as mentors of undergraduate and graduate researchers, medical students, fellows, and early career faculty. Rules 1–5 are big picture recommendations. Rules 6–8 relate to philosophy of reading. Rules 9–10 guide the “now what?” questions one should ask after reading and how to integrate what was learned into one’s own science.

Rule 1: Pick your reading goal

What you want to get out of an article should influence your approach to reading it. Table 1 includes a handful of example intentions and how you might prioritize different parts of the same article differently based on your goals as a reader.

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https://doi.org/10.1371/journal.pcbi.1008032.t001

Rule 2: Understand the author’s goal

In written communication, the reader and the writer are equally important. Both influence the final outcome: in this case, your scientific understanding! After identifying your goal, think about the author’s goal for sharing this project. This will help you interpret the data and understand the author’s interpretation of the data. However, this requires some understanding of who the author(s) are (e.g., what are their scientific interests?), the scientific field in which they work (e.g., what techniques are available in this field?), and how this paper fits into the author’s research (e.g., is this work building on an author’s longstanding project or controversial idea?). This information may be hard to glean without experience and a history of reading. But don’t let this be a discouragement to starting the process; it is by the act of reading that this experience is gained!

A good step toward understanding the goal of the author(s) is to ask yourself: What kind of article is this? Journals publish different types of articles, including methods, review, commentary, resources, and research articles as well as other types that are specific to a particular journal or groups of journals. These article types have different formatting requirements and expectations for content. Knowing the article type will help guide your evaluation of the information presented. Is the article a methods paper, presenting a new technique? Is the article a review article, intended to summarize a field or problem? Is it a commentary, intended to take a stand on a controversy or give a big picture perspective on a problem? Is it a resource article, presenting a new tool or data set for others to use? Is it a research article, written to present new data and the authors’ interpretation of those data? The type of paper, and its intended purpose, will get you on your way to understanding the author’s goal.

Rule 3: Ask six questions

When reading, ask yourself: (1) What do the author(s) want to know (motivation)? (2) What did they do (approach/methods)? (3) Why was it done that way (context within the field)? (4) What do the results show (figures and data tables)? (5) How did the author(s) interpret the results (interpretation/discussion)? (6) What should be done next? (Regarding this last question, the author(s) may provide some suggestions in the discussion, but the key is to ask yourself what you think should come next.)

Each of these questions can and should be asked about the complete work as well as each table, figure, or experiment within the paper. Early on, it can take a long time to read one article front to back, and this can be intimidating. Break down your understanding of each section of the work with these questions to make the effort more manageable.

Rule 4: Unpack each figure and table

Scientists write original research papers primarily to present new data that may change or reinforce the collective knowledge of a field. Therefore, the most important parts of this type of scientific paper are the data. Some people like to scrutinize the figures and tables (including legends) before reading any of the “main text”: because all of the important information should be obtained through the data. Others prefer to read through the results section while sequentially examining the figures and tables as they are addressed in the text. There is no correct or incorrect approach: Try both to see what works best for you. The key is making sure that one understands the presented data and how it was obtained.

For each figure, work to understand each x- and y-axes, color scheme, statistical approach (if one was used), and why the particular plotting approach was used. For each table, identify what experimental groups and variables are presented. Identify what is shown and how the data were collected. This is typically summarized in the legend or caption but often requires digging deeper into the methods: Do not be afraid to refer back to the methods section frequently to ensure a full understanding of how the presented data were obtained. Again, ask the questions in Rule 3 for each figure or panel and conclude with articulating the “take home” message.

Rule 5: Understand the formatting intentions

Just like the overall intent of the article (discussed in Rule 2), the intent of each section within a research article can guide your interpretation. Some sections are intended to be written as objective descriptions of the data (i.e., the Results section), whereas other sections are intended to present the author’s interpretation of the data. Remember though that even “objective” sections are written by and, therefore, influenced by the authors interpretations. Check out Table 2 to understand the intent of each section of a research article. When reading a specific paper, you can also refer to the journal’s website to understand the formatting intentions. The “For Authors” section of a website will have some nitty gritty information that is less relevant for the reader (like word counts) but will also summarize what the journal editors expect in each section. This will help to familiarize you with the goal of each article section.

https://doi.org/10.1371/journal.pcbi.1008032.t002

Rule 6: Be critical

Published papers are not truths etched in stone. Published papers in high impact journals are not truths etched in stone. Published papers by bigwigs in the field are not truths etched in stone. Published papers that seem to agree with your own hypothesis or data are not etched in stone. Published papers that seem to refute your hypothesis or data are not etched in stone.

Science is a never-ending work in progress, and it is essential that the reader pushes back against the author’s interpretation to test the strength of their conclusions. Everyone has their own perspective and may interpret the same data in different ways. Mistakes are sometimes published, but more often these apparent errors are due to other factors such as limitations of a methodology and other limits to generalizability (selection bias, unaddressed, or unappreciated confounders). When reading a paper, it is important to consider if these factors are pertinent.

Critical thinking is a tough skill to learn but ultimately boils down to evaluating data while minimizing biases. Ask yourself: Are there other, equally likely, explanations for what is observed? In addition to paying close attention to potential biases of the study or author(s), a reader should also be alert to one’s own preceding perspective (and biases). Take time to ask oneself: Do I find this paper compelling because it affirms something I already think (or wish) is true? Or am I discounting their findings because it differs from what I expect or from my own work?

The phenomenon of a self-fulfilling prophecy, or expectancy, is well studied in the psychology literature [ 2 ] and is why many studies are conducted in a “blinded” manner [ 3 ]. It refers to the idea that a person may assume something to be true and their resultant behavior aligns to make it true. In other words, as humans and scientists, we often find exactly what we are looking for. A scientist may only test their hypotheses and fail to evaluate alternative hypotheses; perhaps, a scientist may not be aware of alternative, less biased ways to test her or his hypothesis that are typically used in different fields. Individuals with different life, academic, and work experiences may think of several alternative hypotheses, all equally supported by the data.

Rule 7: Be kind

The author(s) are human too. So, whenever possible, give them the benefit of the doubt. An author may write a phrase differently than you would, forcing you to reread the sentence to understand it. Someone in your field may neglect to cite your paper because of a reference count limit. A figure panel may be misreferenced as Supplemental Fig 3E when it is obviously Supplemental Fig 4E. While these things may be frustrating, none are an indication that the quality of work is poor. Try to avoid letting these minor things influence your evaluation and interpretation of the work.

Similarly, if you intend to share your critique with others, be extra kind. An author (especially the lead author) may invest years of their time into a single paper. Hearing a kindly phrased critique can be difficult but constructive. Hearing a rude, brusque, or mean-spirited critique can be heartbreaking, especially for young scientists or those seeking to establish their place within a field and who may worry that they do not belong.

Rule 8: Be ready to go the extra mile

To truly understand a scientific work, you often will need to look up a term, dig into the supplemental materials, or read one or more of the cited references. This process takes time. Some advisors recommend reading an article three times: The first time, simply read without the pressure of understanding or critiquing the work. For the second time, aim to understand the paper. For the third read through, take notes.

Some people engage with a paper by printing it out and writing all over it. The reader might write question marks in the margins to mark parts (s)he wants to return to, circle unfamiliar terms (and then actually look them up!), highlight or underline important statements, and draw arrows linking figures and the corresponding interpretation in the discussion. Not everyone needs a paper copy to engage in the reading process but, whatever your version of “printing it out” is, do it.

Rule 9: Talk about it

Talking about an article in a journal club or more informal environment forces active reading and participation with the material. Studies show that teaching is one of the best ways to learn and that teachers learn the material even better as the teaching task becomes more complex [ 4 – 5 ]; anecdotally, such observations inspired the phrase “to teach is to learn twice.”

Beyond formal settings such as journal clubs, lab meetings, and academic classes, discuss papers with your peers, mentors, and colleagues in person or electronically. Twitter and other social media platforms have become excellent resources for discussing papers with other scientists, the public or your nonscientist friends, or even the paper’s author(s). Describing a paper can be done at multiple levels and your description can contain all of the scientific details, only the big picture summary, or perhaps the implications for the average person in your community. All of these descriptions will solidify your understanding, while highlighting gaps in your knowledge and informing those around you.

Rule 10: Build on it

One approach we like to use for communicating how we build on the scientific literature is by starting research presentations with an image depicting a wall of Lego bricks. Each brick is labeled with the reference for a paper, and the wall highlights the body of literature on which the work is built. We describe the work and conclusions of each paper represented by a labeled brick and discuss each brick and the wall as a whole. The top brick on the wall is left blank: We aspire to build on this work and label this brick with our own work. We then delve into our own research, discoveries, and the conclusions it inspires. We finish our presentations with the image of the Legos and summarize our presentation on that empty brick.

Whether you are reading an article to understand a new topic area or to move a research project forward, effective learning requires that you integrate knowledge from multiple sources (“click” those Lego bricks together) and build upwards. Leveraging published work will enable you to build a stronger and taller structure. The first row of bricks is more stable once a second row is assembled on top of it and so on and so forth. Moreover, the Lego construction will become taller and larger if you build upon the work of others, rather than using only your own bricks.

Build on the article you read by thinking about how it connects to ideas described in other papers and within own work, implementing a technique in your own research, or attempting to challenge or support the hypothesis of the author(s) with a more extensive literature review. Integrate the techniques and scientific conclusions learned from an article into your own research or perspective in the classroom or research lab. You may find that this process strengthens your understanding, leads you toward new and unexpected interests or research questions, or returns you back to the original article with new questions and critiques of the work. All of these experiences are part of the “active reading”: process and are signs of a successful reading experience.

In summary, practice these rules to learn how to read a scientific article, keeping in mind that this process will get easier (and faster) with experience. We are firm believers that an hour in the library will save a week at the bench; this diligent practice will ultimately make you both a more knowledgeable and productive scientist. As you develop the skills to read an article, try to also foster good reading and learning habits for yourself (recommendations here: [ 6 ] and [ 7 ], respectively) and in others. Good luck and happy reading!

Acknowledgments

Thank you to the mentors, teachers, and students who have shaped our thoughts on reading, learning, and what science is all about.

• 1. Brown E. The Weird Sisters. G. P. Putnam’s Sons; 2011.
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Can a New Reading Assessment Tool Help Improve Literacy Rates?

Commentary / 12 April 2024

The Rapid Online Assessment of Reading (ROAR) bridges the lab, the classroom, and the community

In order to understand this article, long ago you went through the laborious (and heroic) process of learning to read . You began by mastering decoding skills—matching sounds to letters, and recognizing words. From there, you conquered comprehension skills, recognizing that words form sentences that create paragraphs like this one. This is an oversimplification, and there are many steps involved in each of these stages, but from a developmental perspective, reading is an iterative skill that builds on mastering previous skills and knowledge.

What if you had missed learning a fundamental skill along the way? And what if none of your teachers or caregivers recognized that gap before you moved on to the next school year? Reading, and learning itself, would become a source of frustration and heartache for you and those trying to teach you. If there were no intervention, your issues would compound—reading skills in early elementary school are predictive of a wide range of outcomes, including high school graduation, college attendance, socioeconomic status, likelihood of encountering the criminal justice system, and long-term health. 

In the U.S., approximately two thirds of students are reading below grade level, and the statistics are particularly distressing among Black, Hispanic, and low-income students. 

In addition, it’s estimated that about 10–15% of children have persistent struggles with reading due to dyslexia. How can we get teachers and administrators the tools they need to meaningfully improve the prospects of the more than 33 million kids who need help with reading?

The Rapid Online Assessment of Reading (ROAR), a project of the Stanford University Reading & Dyslexia Research Program and a recipient of Stage 2: Test Solutions funding from Stanford Impact Labs, is an online assessment platform and research project that aims to make reading assessment free, fun to take, and useful for teachers, administrators, and researchers. 

“Our overarching vision is to create a bridge between research and practice—as we work to develop more efficient and rigorously validated measures of reading development,” said Jason D. Yeatman , Associate Professor of Education and Pediatrics and the ROAR Program Director. “We want to make sure this research stays grounded in real-world problems faced by teachers and administrators and reflects the true diversity of learners at each stage of development. It’s a new model that bridges the lab, classroom, and community.”

Carrie Townley-Flores , Director of Research & Partnerships with ROAR, says, “Stanford Impact Labs funding has helped us tremendously in terms of scaling. We’re in a labor-intensive phase that requires simultaneous work on refining the technology and building relationships with partners so we can iterate the best tool possible and ultimately help as many kids as we can.” 

Improving and Expanding Assessment

ROAR improves on traditional reading assessment in a number of ways. It’s easy to administer, and it has validated assessments for years K–12. By offering a variety of test options, it provides more detailed and reliable results than other standardized assessments and the validation studies underlying the assessments are published in open-access, peer-reviewed scientific journals. Additionally, it’s free, which allows more schools to access the program and encourages flexibility with testing. For example, it makes it easy to test a middle school or high school student for foundational skills, which are typically not assessed after third grade. Students also report it is fun to engage with -- which goes a long way.

Ryland Adzich, project manager for ROAR at San Francisco City Academy (SFCA), a small private school of 60 kids who live in the city's notoriously under-resourced Tenderloin district, said that when SFCA administered the ROAR for the first time in the fall of 2023, students loved it. “The ROAR is set up like a video game, where a character like a monkey or a lion talks to you and guides you through the test. To the students, it felt like a fun, interactive game. This helped promote a positive testing environment where students could perform at their best.”

Adzich also added, “The test is also available in Spanish, and given that more than half our students are Hispanic, we had a handful take the ROAR in Spanish. This allowed us to see that these students don’t have trouble with reading skills, they need a different kind of support. We also tested our middle school kids and identified some areas of struggle that surprised us.” 

SFCA will be administering tests again, along with a new test on letters for younger kids, in the spring of 2024. Using the data from the two testing rounds, along with support from ROAR research coordinators, SFCA’s teachers and administrators will then decide how to implement interventions into the curriculum for the following school year. 

Creating a Virtuous Feedback Cycle

“Our research-practice partnership model brings collaborators into each stage of the research process and it has allowed us to bring innovations to stakeholders much faster than the typical laboratory research model,” said Yeatman. 

“Key to this process is sharing data with the schools and getting feedback from them on the tool so we can iterate and improve on what we’re offering,” said Townley-Flores. For example, the ROAR team recently created interactive score reports to be even more customizable and user friendly. “We got a lot of feedback from schools about what data would be useful and how best to visualize it. This feedback was critical to how we rebuilt the reporting system.”

Feedback to the lab has also resulted in the development of new assessment modules (e.g., letters, morphology), and is expanding the reach of the tool. Rebecca Sutherland , Associate Director of Research with Reading Reimagined, one of ROAR’s partners, explained, “ROAR is going to partner with an expert in Black American English to undertake a rigorous and innovative item analysis to reduce the tests' bias. Too often, standardized literacy assessments unreasonably penalize dialect speakers and underestimate their language and reading skills. This will be a game changer, showing the wider reading assessment field that linguistic bias reduction can and should be done.” 

Through this virtuous feedback cycle, ROAR is looking to continue to improve the tool with the goal of reaching 500,000 students within two years and seeing measurable improvement in reading proficiency, including reduced racial, ethnic, and economic achievement disparities in schools that use ROAR, within 5 to 10 years.

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Computer Science > Artificial Intelligence

Title: rd2bench: toward data-centric automatic r&d.

Abstract: The progress of humanity is driven by those successful discoveries accompanied by countless failed experiments. Researchers often seek the potential research directions by reading and then verifying them through experiments. The process imposes a significant burden on researchers. In the past decade, the data-driven black-box deep learning method demonstrates its effectiveness in a wide range of real-world scenarios, which exacerbates the experimental burden of researchers and thus renders the potential successful discoveries veiled. Therefore, automating such a research and development (R&D) process is an urgent need. In this paper, we serve as the first effort to formalize the goal by proposing a Real-world Data-centric automatic R&D Benchmark, namely RD2Bench. RD2Bench benchmarks all the operations in data-centric automatic R&D (D-CARD) as a whole to navigate future work toward our goal directly. We focuses on evaluating the interaction and synergistic effects of various model capabilities and aiding to select the well-performed trustworthy models. Although RD2Bench is very challenging to the state-of-the-art (SOTA) large language model (LLM) named GPT-4, indicating ample research opportunities and more research efforts, LLMs possess promising potential to bring more significant development to D-CARD: They are able to implement some simple methods without adopting any additional techniques. We appeal to future work to take developing techniques for tackling automatic R&D into consideration, thus bringing the opportunities of the potential revolutionary upgrade to human productivity.

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