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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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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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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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Next: Narrowing a Topic Idea >>
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May 9th, 2016

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

95 comments | 1990 shares

Estimated reading time: 7 minutes

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

Before you begin: some general advice

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

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

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?

4. Identify the SPECIFIC QUESTION(S)

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.

Image credit: author

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?

9. Read the conclusion/discussion/Interpretation section.

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.

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

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)

About the Author

About the author

95 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

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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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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 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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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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This scientist read a paper every day for 899 days. Here’s what she learned

Olivia Rissland says reading a different paper every day has made her a better scientist.

Natalie Parletta

Olivia Rissland says that her reading habits have made her "a much more well-rounded scientist". Credit: Olivia Rissland

8 September 2020

Olivia Rissland

Olivia Rissland says that her reading habits have made her "a much more well-rounded scientist".

Keeping up with the research literature is a must for any scientist, but it tends to slip down the priority list when there’s grant-writing, fieldwork, publishing, teaching, and analysis to be done.

“Reading papers definitely falls under that ‘important and not urgent’ category of activities,” says molecular biologist Olivia Rissland, who runs a lab focussed on understanding gene regulation at the University of Colorado Anschutz Medical Campus in Aurora.

“It’s easy to say, ‘I’ll read that paper tomorrow,’ and then, how much time goes by and you haven’t read a single paper?”

On 1 January 2018, Rissland set herself the task of reading one paper per day, every day, as “a bit of a lark”.

“I thought, ‘Let’s see how long I can keep this up’, but within a month I was hooked,” she says. “I loved the exercise of learning something new every day and seeing how that opened up ideas in my own research.”

By June 17 2020, Rissland announced on Twitter that not only had she had kept the habit up, but it’s benefited her career in ways she couldn’t have predicted.

“As of today, I have read 899 papers in 899 days,” she tweeted. “I never would have imagined 2.5 years ago how much I would learn through this and how this would make me a better scientist and human."

Well-rounded

As well as keeping up with new research in her own field, Rissland now reads more broadly. She’s been pursing literature about the ethical and professional considerations in research, for example, such as the effects of systematic bias on promotion and hiring decisions.

Reading a paper from end to end has also helped her appreciate the nuances that would be missed by skimming the key findings of a paper, such as learning about different scientific methods.

“It’s made me a much more well-rounded scientist,” she says.

While Rissland says there’s no particular strategy guiding her choice of paper, she has a ‘to read’ folder on her computer, which currently has around 250 papers in it. “On most days I choose ones that strike my fancy,” she says.

“Sometimes there are topics that I want to take deep dives into, so I might focus on a topic for a few weeks. But I think part of the fun for me is just to read something that I want to, as opposed to something I have to.”

Rissland says her favourite paper of all time is “ The Mundanity of Excellence ”, a sociology paper about what makes swimmers excel. She says this paper “transformed how I approach science and running a lab”.

Habit-forming

Rissland made the habit stick by holding herself accountable – she shares insights from her daily reads on her lab’s Slack channel, ‘365 papers’.

She also keeps a record of the papers she reads on a Google sheet, which has a line for every day of the year.

“Adding each citation to the Google sheet gives me enough joy and a feeling of accomplishment that it keeps me going,” she says.

Rissland doesn’t cut herself any slack – peer review or sourcing references for her own publications don’t count towards her daily tally. And if she misses one day, or ten, such as when she goes on a family hiking trip, she makes up for it later.

“Dedicating time to reading papers is more important to my lab’s success than answering e-mails,” she says. “I don’t necessarily work more than anyone else, I just make sure I dedicate a set amount of time to reading every day. Rather than being a burden, most of the time this is a high point of my day.”

Rissland’s advice to other researchers who want to take up the challenge is to figure out a routine that’s realistic for them – especially students who read more slowly – such as dedicating 20 or 30 minutes a day to reading.

She also recommends setting realistic guidelines early on, which can help solidify the habit. “The hard ‘structure’ of it keeps me honest,” she says.

Above all, says Rissland, it has to be enjoyable.

“Most of the time it’s the nicest part of my day because I’m actually being a scientist, reading other people’s beautiful research,” she says. “I usually come away feeling really inspired and full of ideas.”

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

Research on Motivation, Literacy and Reading Development: A Review of Best Practices cover

Final Report for the Institute of Museum and Library Services

Literacy development in the early childhood and elementary school years is critical for learning and the acquisition of other skills essential for educational achievement. Although schools typically assume the primary responsibility in developing children’s literacy and reading skills, a holistic approach to overall literacy development requires the involvement of other important actors, including parents, caregivers, community members, and libraries. Public libraries play a key role in the literacy landscape, especially by providing access to books and a variety of free literacy programs for families. The public library as a space and place that motivates kids to enjoy reading can lead to a lifelong love of learning. In summer 2023, IMLS commissioned a review of research literature that examines the effects of motivation to read and within reading programs in communities and, particularly, public libraries.

Key findings from this literature review identify research studies that focused on the effectiveness of reading strategies that emphasized motivations when promoting reading. This study summarizes several evidence-based practices tied to increasing motivation used during programs, instructional practices, and family engagement activities which are focused on child literacy and community participation.

Iowa Reading Research Center

Research Article of the Month: April 2024

This blog post is part of our Research Article of the Month series. For this month, we highlight “ Designing an Intervention in Reading and Self-Regulation for Students With Significant Reading Difficulties Including Dyslexia ,” an article published in the journal Learning Disability Quarterly in 2021. Important words related to research are bolded, and definitions of these terms are included at the end of the article in the “Terms to Know” section.

Why Did We Pick This Paper?

Self-regulation is the ability to modify one’s thinking, emotions, and behavior to achieve a goal. Some self-regulation strategies include setting goals, becoming aware of emotions, practicing positive self-statements (“I am doing my best” or “I will not give up”), and believing in the ability to grow and learn.

Self-regulation contributes to reading proficiency (Berkeley & Larson, 2018), and students with reading difficulties tend to have impaired self-regulation (Cutting, et al., 2009). Fortunately, training in self-regulation has been shown to improve the use of self-regulation strategies and reading comprehension outcomes (Spörer & Schünemann, 2014). This study examined the feasibility and effects of a reading intervention that explicitly teaches self-regulation strategies. Reading interventions that target self-regulation may support the reading outcomes of students with reading disabilities (RDs).

What Are the Research Questions or Purpose?

This study examined the feasibility of implementing a specific reading intervention with self-regulation instruction by addressing the following questions:

Is the intervention associated with stronger effects on reading outcomes than the interventions currently provided to students with RDs in the participating schools?
Can teachers implement the intervention as designed?
What are the barriers to consistent implementation and to student progress in the intervention?
What are teachers’ perceptions of the self-regulation component of the intervention?
What parts of the intervention should be maintained as they are and how should the intervention be revised?

What Methodology Do the Authors Employ?

To assess the feasibility of the intervention and explore its potential effects on reading outcomes, the study employed a quasi-experimental design.

A group of special education teachers, dyslexia specialists, and reading interventionists were randomly assigned to teach the intervention (the experimental condition) or continue delivering their typical instruction (the business-as-usual , or BAU, condition). Instruction was delivered in small groups of 2-4 students, 4 days a week for 26 weeks.

A total of 21 instructors participated in the study (10 in the intervention and 11 in the BAU condition), as well as 43 students in Grades 2-4 (23 in the intervention and 20 in the BAU condition).

The students were assessed on a number of reading skills, including word recognition, decoding, reading comprehension, and oral reading fluency, at the beginning and end of the study. Pre- and post-test scores were compared in order to assess students’ growth in the measured skills over the course of the study.

The intervention consisted of word study, text reading, reading comprehension, and self-regulation, as described below:

Word study: The word study component included instruction in phonemic awareness, decoding, word recognition, and spelling.
Text reading: For the text-reading component, students read high-interest, motivating decodable texts that included phonics and spelling patterns the students had been explicitly taught. They also applied these skills on authentic texts to practice extending these skills to new contexts.
Comprehension: The comprehension component included guiding questions to focus students’ attention and activate prior knowledge. Teachers asked questions that would stimulate students to recall events, generate inferences, make connections across texts, paraphrase, identify main ideas, monitor their understanding, generate questions, and visualize. Teachers modeled comprehension skills and provided students with multiple practice opportunities.
Self-regulation: The self-regulation component included activities designed to support a growth mindset (the belief that one can grow and achieve success in the future despite present challenges), emotional self-regulation (the ability to identify emotions), reflection on comprehension strategy use, positive self-statements, and goal setting.

These components were delivered in two phases: the first phase focused on foundational reading skills, and the second phase addressed more advanced skills. For all components, students received direct instruction and modeling from teachers, and they practiced skills using multiple modalities (e.g., reading, writing, and manipulation of letter tiles).

Students in the BAU condition received instruction using other evidence-based programs.

The researchers monitored the fidelity and quality of implementation for the intervention by recording videos of classroom instruction. The researchers conducted an analysis of covariance with pre- and post-test scores to determine whether the intervention was associated with greater effects than traditional instruction. The intervention teachers also participated in two focus groups to provide feedback on the feasibility of the intervention.

What Are the Key Findings?

Research question 1: is the intervention associated with stronger effects on reading outcomes than the interventions currently provided to students with rds in the participating schools.

Students’ pre-test scores on all reading skill variables were higher in the BAU condition compared to the experimental condition, but there were no significant differences between groups for any measures on the post-test. Thus, the intervention was not associated with stronger effects on reading outcomes than other interventions used in the participating schools.

Research Question 2: Can teachers implement the intervention as designed?

The fidelity and quality of implementation were reported as a percentage to measure if the intervention was implemented as designed. The mean word study and text reading fidelity rating was 88%, and the quality rating was 92%. For comprehension and self-regulation, the mean fidelity rating was 81%, and the quality rating was 94%. The lower fidelity rating for the comprehension and self-regulation components indicates that these components were more difficult for teachers to implement as intended.

Research Question 3: What are the barriers to consistent implementation and to student progress in the intervention?

Teachers identified context barriers, including scheduling, limited school resources, limited instructional and planning time, and logistics related to providing the intervention at two different schools on the same day. They also identified student-related barriers, including student frustration with literacy tasks, lack of confidence and inconsistent focus, and behavior management.

Research Question 4: What are teachers’ perceptions of the self-regulation component of the intervention?

In focus groups, teachers voiced their support for the self-regulation component of the intervention, citing the positive effects of growth mindset instruction on students’ confidence and self-esteem. Teachers also noted the benefits of recognizing negative self-statements and substituting them with positive ones.

Research Question 5: What parts of the intervention should be maintained as they are and how should the intervention be revised?

The teachers requested a better approach for organizing and managing materials (e.g., letter tiles, books, visual aids). They suggested that future versions of the intervention should focus more on active student participation rather than teacher talk. They wanted a stronger fluency component of the intervention and guidance on incorporating technology into instruction. Overall, the teachers highlighted that the strengths of the intervention include its well-designed curriculum and content, the material resources provided, and the variety of activities that support student interest and participation.

What Are the Limitations of This Paper?

The study examined the implementation of a multi-component intervention for reading and self-regulation for students with RDs. Teachers highlighted several challenges they faced in implementing this intervention, including managing materials and coordinating the pace of the different lesson components. This complexity could potentially limit the intervention’s ease of implementation, as educators may struggle to implement it effectively without substantial preparatory training or additional support and technology. Enhancing teacher readiness through targeted professional development sessions, along with providing ongoing support and technology, could improve the fidelity and quality of implementing of this complex intervention.

Additionally, the study was constrained by its small sample size, which limits the statistical power in detecting the possible effectiveness of the intervention. A small number of participants can make it challenging to detect smaller but statistically significant effect sizes or subtle differences between treatment and BAU groups. For further research on the effectiveness of the intervention, a greater number of participants is needed to validate the results and conclusions drawn from this study.

Terms to Know

Feasibility: A feasibility study follows the implementation of a project or process (such as a new reading instructional program) in order to assess its potential for success. Researchers may gather data and feedback to inform future revisions.
Quasi-experimental: Experimental research aims to determine whether a certain treatment influences a measurable outcome—for example, whether a certain instructional method influences students’ reading comprehension scores. To do this, participants are assigned to one of two groups: the experimental group, which receives the treatment, and the control group, which does not receive the treatment. In an experimental study, these groups are randomly assigned, meaning each participant has equal probability of being in either the treatment or the control group. A quasi-experimental study is similar to an experimental study except that participants are not randomly assigned to groups. In educational research, groups often are assigned by classroom rather than through random assignment, making this kind of research quasi-experimental. In either case, participants in both groups are tested before and after the treatment, and their results are compared.
Business-as-usual (BAU) condition: The business-as-usual condition is another name for the control group in an experimental or quasi-experimental study. This group does not receive the experimental treatment and therefore serves as a point of comparison for the experimental group.
Fidelity: Fidelity is a measure of the extent to which a process, such as an instructional approach, is implemented as intended.
Covariance: Covariance , in statistics, is a measure of the relationship between two variables and the extent to which they change together.
Effects: In statistics, effect size is a measure of the strength of the relationship between two variables in statistical analyses. A commonly used interpretation is to refer to effect size as small (g = 0.2), medium (g = 0.5), and large (g = 0.8) based on the benchmarks suggested by Cohen (1988), where “g” refers to Hedge’s g, a statistical measure of effect size.
Focus groups: A focus group gathers participants for a guided discussion or interview in order to elicit feedback about a product or process.

Berkeley, S., & Larsen, A. (2018). Fostering self–regulation of students with learning disabilities: Insights from 30 years of reading comprehension intervention research. Learning Disabilities Research & Practice , 33 (2), 75-86. https://doi.org/10.1111/ldrp.12165

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Routledge Academic.

Cutting, L. E., Materek, A., Cole, C. A. S., Levine, T. M., & Mahone, E. M. (2009). Effects of fluency, oral language, and executive function on reading comprehension performance. Annals of Dyslexia , 59, 34–54. https://doi.org/10.1007/s11881-009-0022-0

Denton, C. A., Montroy, J. J., Zucker, T. A., Cannon, G. (2021). Designing an intervention in reading and self-regulation for students with significant reading difficulties, including dyslexia. Learning Disability Quarterly , 44 (3), 170-182. https://doi.org/10.1177/0731948719899479

Spörer, N., & Schünemann, N. (2014). Improvements of self-regulation procedures for fifth graders' reading competence: Analyzing effects on reading comprehension, reading strategy performance, and motivation for reading. Learning and Instruction , 33 , 147-157. https://doi.org/10.1016/j.learninstruc.2014.05.002

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Some scientists can't stop using AI to write research papers

If you read about 'meticulous commendable intricacy' there's a chance a boffin had help.

Linguistic and statistical analyses of scientific articles suggest that generative AI may have been used to write an increasing amount of scientific literature.

Two academic papers assert that analyzing word choice in the corpus of science publications reveals an increasing usage of AI for writing research papers. One study , published in March by Andrew Gray of University College London in the UK, suggests at least one percent – 60,000 or more – of all papers published in 2023 were written at least partially by AI.

A second paper published in April by a Stanford University team in the US claims this figure might range between 6.3 and 17.5 percent, depending on the topic.

Both papers looked for certain words that large language models (LLMs) use habitually, such as “intricate,” “pivotal,” and “meticulously." By tracking the use of those words across scientific literature, and comparing this to words that aren't particularly favored by AI, the two studies say they can detect an increasing reliance on machine learning within the scientific publishing community.

In Gray's paper, the use of control words like "red," "conclusion," and "after" changed by a few percent from 2019 to 2023. The same was true of other certain adjectives and adverbs until 2023 (termed the post-LLM year by Gray).

In that year use of the words "meticulous," "commendable," and "intricate," rose by 59, 83, and 117 percent respectively, while their prevalence in scientific literature hardly changed between 2019 and 2022. The word with the single biggest increase in prevalence post-2022 was “meticulously”, up 137 percent.

The Stanford paper found similar phenomena, demonstrating a sudden increase for the words "realm," "showcasing," "intricate," and "pivotal." The former two were used about 80 percent more often than in 2021 and 2022, while the latter two were used around 120 and almost 160 percent more frequently respectively.

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The researchers also considered word usage statistics in various scientific disciplines. Computer science and electrical engineering were ahead of the pack when it came to using AI-preferred language, while mathematics, physics, and papers published by the journal Nature, only saw increases of between five and 7.5 percent.

The Stanford bods also noted that authors posting more preprints, working in more crowded fields, and writing shorter papers seem to use AI more frequently. Their paper suggests that a general lack of time and a need to write as much as possible encourages the use of LLMs, which can help increase output.

Potentially the next big controversy in the scientific community

Using AI to help in the research process isn't anything new, and lots of boffins are open about utilizing AI to tweak experiments to achieve better results. However, using AI to actually write abstracts and other chunks of papers is very different, because the general expectation is that scientific articles are written by actual humans, not robots, and at least a couple of publishers consider using LLMs to write papers to be scientific misconduct.

Using AI models can be very risky as they often produce inaccurate text, the very thing scientific literature is not supposed to do. AI models can even fabricate quotations and citations, an occurrence that infamously got two New York attorneys in trouble for citing cases ChatGPT had dreamed up.

"Authors who are using LLM-generated text must be pressured to disclose this or to think twice about whether doing so is appropriate in the first place, as a matter of basic research integrity," University College London’s Gray opined.

The Stanford researchers also raised similar concerns, writing that use of generative AI in scientific literature could create "risks to the security and independence of scientific practice." ®

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Microsoft Research Blog

Microsoft at asplos 2024: advancing hardware and software for high-scale, secure, and efficient modern applications.

Published April 29, 2024

By Rodrigo Fonseca , Sr Principal Research Manager Madan Musuvathi , Partner Research Manager

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Modern computer systems and applications, with unprecedented scale, complexity, and security needs, require careful co-design and co-evolution of hardware and software. The ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) (opens in new tab) , is the main forum where researchers bridge the gap between architecture, programming languages, and operating systems to advance the state of the art.

ASPLOS 2024 is taking place in San Diego between April 27 and May 1, and Microsoft researchers and collaborators have a strong presence, with members of our team taking on key roles in organizing the event. This includes participation in the program and external review committees and leadership as the program co-chair.

We are pleased to share that eight papers from Microsoft researchers and their collaborators have been accepted to the conference, spanning a broad spectrum of topics. In the field of AI and deep learning, subjects include power and frequency management for GPUs and LLMs, the use of Process-in-Memory for deep learning, and instrumentation frameworks. Regarding infrastructure, topics include memory safety with CHERI, I/O prefetching in modern storage, and smart oversubscription of burstable virtual machines. This post highlights some of this work.

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AI Frontiers: The future of scale with Ahmed Awadallah and Ashley Llorens

This episode features Senior Principal Research Manager Ahmed H. Awadallah , whose work improving the efficiency of large-scale AI models and efforts to help move advancements in the space from research to practice have put him at the forefront of this new era of AI.

Paper highlights

Characterizing power management opportunities for llms in the cloud.

The rising popularity of LLMs and generative AI has led to an unprecedented demand for GPUs. However, the availability of power is a key limiting factor in expanding a GPU fleet. This paper characterizes the power usage in LLM clusters, examines the power consumption patterns across multiple LLMs, and identifies the differences between inference and training power consumption patterns. This investigation reveals that the average and peak power consumption in inference clusters is not very high, and that there is substantial headroom for power oversubscription. Consequently, the authors propose POLCA: a framework for power oversubscription that is robust, reliable, and readily deployable for GPU clusters. It can deploy 30% more servers in the same GPU clusters for inference tasks, with minimal performance degradation.

PIM-DL: Expanding the Applicability of Commodity DRAM-PIMs for Deep Learning via Algorithm-System Co-Optimization

PIM-DL is the first deep learning framework specifically designed for off-the-shelf processing-in-memory (PIM) systems, capable of offloading most computations in neural networks. Its goal is to surmount the computational limitations of PIM hardware by replacing traditional compute-heavy matrix multiplication operations with Lookup Tables (LUTs). PIM-DL first enables neural networks to operate efficiently on PIM architectures, significantly reducing the need for complex arithmetic operations. PIM-DL demonstrates significant speed improvements, achieving up to ~37x faster performance than traditional GEMM-based systems and showing competitive speedups against CPUs and GPUs.

Cornucopia Reloaded: Load Barriers for CHERI Heap Temporal Safety

Memory safety bugs have persistently plagued software for over 50 years and underpin some 70% of common vulnerabilities and exposures (CVEs) every year. The CHERI capability architecture (opens in new tab) is an emerging technology (opens in new tab) (especially through Arm’s Morello (opens in new tab) and Microsoft’s CHERIoT (opens in new tab) platforms) for spatial memory safety and software compartmentalization. In this paper, the authors demonstrate the viability of object-granularity heap temporal safety built atop CHERI with considerably lower overheads than prior work.

AUDIBLE: A Convolution-Based Resource Allocator for Oversubscribing Burstable Virtual Machines

Burstable virtual machines (BVMs) are a type of virtual machine in the cloud that allows temporary increases in resource allocation. This paper shows how to oversubscribe BVMs. It first studies the characteristics of BVMs on Microsoft Azure and explains why traditional approaches based on using a fixed oversubscription ratio or based on the Central Limit Theorem do not work well for BVMs: they lead to either low utilization or high server capacity violation rates. Based on the lessons learned from the workload study, the authors developed a new approach, called AUDIBLE, using a nonparametric statistical model. This makes the approach lightweight and workload independent. This study shows that AUDIBLE achieves high system utilization while enforcing stringent requirements on server capacity violations.

Complete list of accepted publications by Microsoft researchers

Amanda: Unified Instrumentation Framework for Deep Neural Networks Yue Guan, Yuxian Qiu, and Jingwen Leng; Fan Yang , Microsoft Research; Shuo Yu, Shanghai Jiao Tong University; Yunxin Liu, Tsinghua University; Yu Feng and Yuhao Zhu, University of Rochester; Lidong Zhou , Microsoft Research; Yun Liang, Peking University; Chen Zhang, Chao Li, and Minyi Guo, Shanghai Jiao Tong University

AUDIBLE: A Convolution-Based Resource Allocator for Oversubscribing Burstable Virtual Machines Seyedali Jokar Jandaghi and Kaveh Mahdaviani, University of Toronto; Amirhossein Mirhosseini, University of Michigan; Sameh Elnikety , Microsoft Research; Cristiana Amza and Bianca Schroeder, University of Toronto, Cristiana Amza and Bianca Schroeder, University of Toronto

Characterizing Power Management Opportunities for LLMs in the Cloud (opens in new tab) Pratyush Patel, Microsoft Azure and University of Washington; Esha Choukse (opens in new tab) , Chaojie Zhang (opens in new tab) , and Íñigo Goiri (opens in new tab) , Azure Research; Brijesh Warrier (opens in new tab) , Nithish Mahalingam, Ricardo Bianchini (opens in new tab) , Microsoft AzureResearch

Cornucopia Reloaded: Load Barriers for CHERI Heap Temporal Safety Nathaniel Wesley Filardo , University of Cambridge and Microsoft Research; Brett F. Gutstein, Jonathan Woodruff, Jessica Clarke, and Peter Rugg, University of Cambridge; Brooks Davis, SRI International; Mark Johnston, University of Cambridge; Robert Norton , Microsoft Research; David Chisnall, SCI Semiconductor; Simon W. Moore, University of Cambridge; Peter G. Neumann, SRI International; Robert N. M. Watson, University of Cambridge

CrossPrefetch: Accelerating I/O Prefetching for Modern Storage Shaleen Garg and Jian Zhang, Rutgers University; Rekha Pitchumani, Samsung; Manish Parashar, University of Utah; Bing Xie , Microsoft; Sudarsun Kannan, Rutgers University

Kimbap: A Node-Property Map System for Distributed Graph Analytics Hochan Lee, University of Texas at Austin; Roshan Dathathri, Microsoft Research; Keshav Pingali, University of Texas at Austin

PIM-DL: Expanding the Applicability of Commodity DRAM-PIMs for Deep Learning via Algorithm-System Co-Optimization Cong Li and Zhe Zhou, Peking University; Yang Wang , Microsoft Research; Fan Yang, Nankai University; Ting Cao and Mao Yang , Microsoft Research; Yun Liang and Guangyu Sun, Peking University

Predict; Don’t React for Enabling Efficient Fine-Grain DVFS in GPUs Srikant Bharadwaj , Microsoft Research; Shomit Das, Qualcomm; Kaushik Mazumdar and Bradford M. Beckmann, AMD; Stephen Kosonocky, Uhnder

Conference organizers from Microsoft

Program co-chair, madan musuvathi, submission chairs.

Jubi Taneja Olli Saarikivi

Program Committee

Abhinav Jangda (opens in new tab) Aditya Kanade (opens in new tab) Ashish Panwar (opens in new tab) Jacob Nelson (opens in new tab) Jay Lorch (opens in new tab) Jilong Xue (opens in new tab) Paolo Costa (opens in new tab) Rodrigo Fonseca (opens in new tab) Shan Lu (opens in new tab) Suman Nath (opens in new tab) Tim Harris (opens in new tab)

External Review Committee

Career opportunities.

Microsoft welcomes talented individuals across various roles at Microsoft Research, Azure Research, and other departments. We are always pushing the boundaries of computer systems to improve the scale, efficiency, and security of all our offerings. You can review our open research-related positions here .

Related publications

Kimbap: a node-property map system for distributed graph analytics, predict; don’t react for enabling efficient fine-grain dvfs in gpus, amanda: unified instrumentation framework for deep neural networks, crossprefetch: accelerating i/o prefetching for modern storage, meet the authors.

Rodrigo Fonseca

Sr Principal Research Manager

Partner Research Manager

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Research Focus: Week of April 15, 2024

"2023 Microsoft Research Year In Review" in white text on a blue, green, and purple abstract gradient background

Research at Microsoft 2023: A year of groundbreaking AI advances and discoveries

Flowchart showing natural language is transformed into a program in domain specific language using an LLM. This step is called Intent formalization. The user is able to modify, repair and query. The Program in DSL is then converted into natural language representation that can be in text or visual formats. The Program in DSL is also separatedly converted into Code via the Code Generation pipeline. This step is called Robust Code Generation.

PwR: Using representations for AI-powered software development

Research Focus: November 22, 2023 on a gradient patterned background

Research Focus: Week of November 22, 2023

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

What is a Research Paper?

What Research Papers are NOT

Why Should You Read Research Papers?

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

ML Reproducibility Challenge

How to Find the Right Paper to Read

How to Read a Research Paper

The three pass approach

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⚠️ Symptoms of Reading a Research Paper

Key Takeaways

Ten simple rules for reading a scientific paper

Introduction

Rule 1: Pick your reading goal

Rule 2: Understand the author’s goal

Rule 3: Ask six questions

Rule 4: Unpack each figure and table

Rule 5: Understand the formatting intentions

Rule 6: Be critical

Rule 7: Be kind

Rule 8: Be ready to go the extra mile

Rule 9: Talk about it

Rule 10: Build on it

Acknowledgments

This scientist read a paper every day for 899 days. Here’s what she learned

Well-rounded

Habit-forming

On reading research papers

A research paper encapsulates enormous effort

A research paper encapsulates a moment in history

A research paper deserves critical attention

You owe a research paper nothing

Concrete reading guides

Public reading groups

Iowa Reading Research Center

Research Article of the Month: April 2024

Why Did We Pick This Paper?

What Are the Research Questions or Purpose?

What Methodology Do the Authors Employ?

What Are the Key Findings?

Research Question 2: Can teachers implement the intervention as designed?

Research Question 3: What are the barriers to consistent implementation and to student progress in the intervention?

Research Question 4: What are teachers’ perceptions of the self-regulation component of the intervention?

Research Question 5: What parts of the intervention should be maintained as they are and how should the intervention be revised?

What Are the Limitations of This Paper?

Terms to Know

Research Article of the Month: March 2024

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Boffins deem Google DeepMind's material discoveries rather shallow

Potentially the next big controversy in the scientific community

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