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How to Write a Conclusion for Research Papers (with Examples)

The conclusion of a research paper is a crucial section that plays a significant role in the overall impact and effectiveness of your research paper. However, this is also the section that typically receives less attention compared to the introduction and the body of the paper. The conclusion serves to provide a concise summary of the key findings, their significance, their implications, and a sense of closure to the study. Discussing how can the findings be applied in real-world scenarios or inform policy, practice, or decision-making is especially valuable to practitioners and policymakers. The research paper conclusion also provides researchers with clear insights and valuable information for their own work, which they can then build on and contribute to the advancement of knowledge in the field.

The research paper conclusion should explain the significance of your findings within the broader context of your field. It restates how your results contribute to the existing body of knowledge and whether they confirm or challenge existing theories or hypotheses. Also, by identifying unanswered questions or areas requiring further investigation, your awareness of the broader research landscape can be demonstrated.

Remember to tailor the research paper conclusion to the specific needs and interests of your intended audience, which may include researchers, practitioners, policymakers, or a combination of these.

What is a conclusion in a research paper, summarizing conclusion, editorial conclusion, externalizing conclusion, importance of a good research paper conclusion, how to write a conclusion for your research paper, research paper conclusion examples.

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Frequently Asked Questions

A conclusion in a research paper is the final section where you summarize and wrap up your research, presenting the key findings and insights derived from your study. The research paper conclusion is not the place to introduce new information or data that was not discussed in the main body of the paper. When working on how to conclude a research paper, remember to stick to summarizing and interpreting existing content. The research paper conclusion serves the following purposes: 1

Warn readers of the possible consequences of not attending to the problem.
Recommend specific course(s) of action.
Restate key ideas to drive home the ultimate point of your research paper.
Provide a “take-home” message that you want the readers to remember about your study.

Types of conclusions for research papers

In research papers, the conclusion provides closure to the reader. The type of research paper conclusion you choose depends on the nature of your study, your goals, and your target audience. I provide you with three common types of conclusions:

A summarizing conclusion is the most common type of conclusion in research papers. It involves summarizing the main points, reiterating the research question, and restating the significance of the findings. This common type of research paper conclusion is used across different disciplines.

An editorial conclusion is less common but can be used in research papers that are focused on proposing or advocating for a particular viewpoint or policy. It involves presenting a strong editorial or opinion based on the research findings and offering recommendations or calls to action.

An externalizing conclusion is a type of conclusion that extends the research beyond the scope of the paper by suggesting potential future research directions or discussing the broader implications of the findings. This type of conclusion is often used in more theoretical or exploratory research papers.

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The conclusion in a research paper serves several important purposes:

Offers Implications and Recommendations : Your research paper conclusion is an excellent place to discuss the broader implications of your research and suggest potential areas for further study. It’s also an opportunity to offer practical recommendations based on your findings.
Provides Closure : A good research paper conclusion provides a sense of closure to your paper. It should leave the reader with a feeling that they have reached the end of a well-structured and thought-provoking research project.
Leaves a Lasting Impression : Writing a well-crafted research paper conclusion leaves a lasting impression on your readers. It’s your final opportunity to leave them with a new idea, a call to action, or a memorable quote.

Writing a strong conclusion for your research paper is essential to leave a lasting impression on your readers. Here’s a step-by-step process to help you create and know what to put in the conclusion of a research paper: 2

Research Statement : Begin your research paper conclusion by restating your research statement. This reminds the reader of the main point you’ve been trying to prove throughout your paper. Keep it concise and clear.
Key Points : Summarize the main arguments and key points you’ve made in your paper. Avoid introducing new information in the research paper conclusion. Instead, provide a concise overview of what you’ve discussed in the body of your paper.
Address the Research Questions : If your research paper is based on specific research questions or hypotheses, briefly address whether you’ve answered them or achieved your research goals. Discuss the significance of your findings in this context.
Significance : Highlight the importance of your research and its relevance in the broader context. Explain why your findings matter and how they contribute to the existing knowledge in your field.
Implications : Explore the practical or theoretical implications of your research. How might your findings impact future research, policy, or real-world applications? Consider the “so what?” question.
Future Research : Offer suggestions for future research in your area. What questions or aspects remain unanswered or warrant further investigation? This shows that your work opens the door for future exploration.
Closing Thought : Conclude your research paper conclusion with a thought-provoking or memorable statement. This can leave a lasting impression on your readers and wrap up your paper effectively. Avoid introducing new information or arguments here.
Proofread and Revise : Carefully proofread your conclusion for grammar, spelling, and clarity. Ensure that your ideas flow smoothly and that your conclusion is coherent and well-structured.

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Remember that a well-crafted research paper conclusion is a reflection of the strength of your research and your ability to communicate its significance effectively. It should leave a lasting impression on your readers and tie together all the threads of your paper. Now you know how to start the conclusion of a research paper and what elements to include to make it impactful, let’s look at a research paper conclusion sample.

How to write a research paper conclusion with Paperpal?

A research paper conclusion is not just a summary of your study, but a synthesis of the key findings that ties the research together and places it in a broader context. A research paper conclusion should be concise, typically around one paragraph in length. However, some complex topics may require a longer conclusion to ensure the reader is left with a clear understanding of the study’s significance. Paperpal, an AI writing assistant trusted by over 800,000 academics globally, can help you write a well-structured conclusion for your research paper.

Sign Up or Log In: Create a new Paperpal account or login with your details.
Navigate to Features : Once logged in, head over to the features’ side navigation pane. Click on Templates and you’ll find a suite of generative AI features to help you write better, faster.
Generate an outline: Under Templates, select ‘Outlines’. Choose ‘Research article’ as your document type.
Select your section: Since you’re focusing on the conclusion, select this section when prompted.
Choose your field of study: Identifying your field of study allows Paperpal to provide more targeted suggestions, ensuring the relevance of your conclusion to your specific area of research.
Provide a brief description of your study: Enter details about your research topic and findings. This information helps Paperpal generate a tailored outline that aligns with your paper’s content.
Generate the conclusion outline: After entering all necessary details, click on ‘generate’. Paperpal will then create a structured outline for your conclusion, to help you start writing and build upon the outline.
Write your conclusion: Use the generated outline to build your conclusion. The outline serves as a guide, ensuring you cover all critical aspects of a strong conclusion, from summarizing key findings to highlighting the research’s implications.
Refine and enhance: Paperpal’s ‘Make Academic’ feature can be particularly useful in the final stages. Select any paragraph of your conclusion and use this feature to elevate the academic tone, ensuring your writing is aligned to the academic journal standards.

By following these steps, Paperpal not only simplifies the process of writing a research paper conclusion but also ensures it is impactful, concise, and aligned with academic standards. Sign up with Paperpal today and write your research paper conclusion 2x faster .

The research paper conclusion is a crucial part of your paper as it provides the final opportunity to leave a strong impression on your readers. In the research paper conclusion, summarize the main points of your research paper by restating your research statement, highlighting the most important findings, addressing the research questions or objectives, explaining the broader context of the study, discussing the significance of your findings, providing recommendations if applicable, and emphasizing the takeaway message. The main purpose of the conclusion is to remind the reader of the main point or argument of your paper and to provide a clear and concise summary of the key findings and their implications. All these elements should feature on your list of what to put in the conclusion of a research paper to create a strong final statement for your work.

A strong conclusion is a critical component of a research paper, as it provides an opportunity to wrap up your arguments, reiterate your main points, and leave a lasting impression on your readers. Here are the key elements of a strong research paper conclusion: 1. Conciseness : A research paper conclusion should be concise and to the point. It should not introduce new information or ideas that were not discussed in the body of the paper. 2. Summarization : The research paper conclusion should be comprehensive enough to give the reader a clear understanding of the research’s main contributions. 3 . Relevance : Ensure that the information included in the research paper conclusion is directly relevant to the research paper’s main topic and objectives; avoid unnecessary details. 4 . Connection to the Introduction : A well-structured research paper conclusion often revisits the key points made in the introduction and shows how the research has addressed the initial questions or objectives. 5. Emphasis : Highlight the significance and implications of your research. Why is your study important? What are the broader implications or applications of your findings? 6 . Call to Action : Include a call to action or a recommendation for future research or action based on your findings.

The length of a research paper conclusion can vary depending on several factors, including the overall length of the paper, the complexity of the research, and the specific journal requirements. While there is no strict rule for the length of a conclusion, but it’s generally advisable to keep it relatively short. A typical research paper conclusion might be around 5-10% of the paper’s total length. For example, if your paper is 10 pages long, the conclusion might be roughly half a page to one page in length.

In general, you do not need to include citations in the research paper conclusion. Citations are typically reserved for the body of the paper to support your arguments and provide evidence for your claims. However, there may be some exceptions to this rule: 1. If you are drawing a direct quote or paraphrasing a specific source in your research paper conclusion, you should include a citation to give proper credit to the original author. 2. If your conclusion refers to or discusses specific research, data, or sources that are crucial to the overall argument, citations can be included to reinforce your conclusion’s validity.

The conclusion of a research paper serves several important purposes: 1. Summarize the Key Points 2. Reinforce the Main Argument 3. Provide Closure 4. Offer Insights or Implications 5. Engage the Reader. 6. Reflect on Limitations

Remember that the primary purpose of the research paper conclusion is to leave a lasting impression on the reader, reinforcing the key points and providing closure to your research. It’s often the last part of the paper that the reader will see, so it should be strong and well-crafted.

Makar, G., Foltz, C., Lendner, M., & Vaccaro, A. R. (2018). How to write effective discussion and conclusion sections. Clinical spine surgery, 31(8), 345-346.
Bunton, D. (2005). The structure of PhD conclusion chapters. Journal of English for academic purposes , 4 (3), 207-224.

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9. The Conclusion
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The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research. For most college-level research papers, two or three well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in describing the key findings and their significance.

Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.

Importance of a Good Conclusion

A well-written conclusion provides you with important opportunities to demonstrate to the reader your understanding of the research problem. These include:

Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize your answer to the "So What?" question by placing the study within the context of how your research advances past research about the topic.
Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [first identified in your literature review section] has been addressed by your research and why this contribution is significant.
Demonstrating the importance of your ideas . Don't be shy. The conclusion offers an opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.

Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Structure and Writing Style

I. General Rules

The general function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Do this by clearly summarizing the context, background, and necessity of pursuing the research problem you investigated in relation to an issue, controversy, or a gap found in the literature. However, make sure that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your paper.

When writing the conclusion to your paper, follow these general rules:

Present your conclusions in clear, concise language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., what were the unique, new, or crucial contributions your study made to the overall research about your topic?].
Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem but that further investigations should take place beyond the scope of your investigation.

Consider the following points to help ensure your conclusion is presented well:

If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data [this is opposite of the introduction, which begins with general discussion of the context and ends with a detailed description of the research problem].

The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way. If asked to think introspectively about the topics, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.

II. Developing a Compelling Conclusion

Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following:

If your essay deals with a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively.
Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge leading to positive change.
Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good source would be from your literature review].
Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results from your study to recast it in new or important ways.
Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.

III. Problems to Avoid

Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .

Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move from a specific discussion [your research problem] back to a general discussion framed around the implications and significance of your findings [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific analysis and discussion, conclude with a broad summary of the study's implications and significance].

Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study. They should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use negative results as an opportunity to explain their possible significance and/or how they may form the basis for future research.

Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long.

Failure to match the objectives of your research Often research objectives in the social and behavioral sciences change while the research is being carried out. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority as a researcher by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader about the study's validity and realiability.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining that they are reaching the end of your paper. You'll irritate your readers if you belabor the obvious.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper. This why the conclusion rarely has citations to sources. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you’ve presented, and position your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights to that scholarship.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.

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Writing Tips

How to Write a Conclusion for a Research Paper

3-minute read

29th August 2023

If you’re writing a research paper, the conclusion is your opportunity to summarize your findings and leave a lasting impression on your readers. In this post, we’ll take you through how to write an effective conclusion for a research paper and how you can:

· Reword your thesis statement

· Highlight the significance of your research

· Discuss limitations

· Connect to the introduction

· End with a thought-provoking statement

Rewording Your Thesis Statement

Begin your conclusion by restating your thesis statement in a way that is slightly different from the wording used in the introduction. Avoid presenting new information or evidence in your conclusion. Just summarize the main points and arguments of your essay and keep this part as concise as possible. Remember that you’ve already covered the in-depth analyses and investigations in the main body paragraphs of your essay, so it’s not necessary to restate these details in the conclusion.

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Highlighting the Significance of Your Research

The conclusion is a good place to emphasize the implications of your research . Avoid ambiguous or vague language such as “I think” or “maybe,” which could weaken your position. Clearly explain why your research is significant and how it contributes to the broader field of study.

Here’s an example from a (fictional) study on the impact of social media on mental health:

Discussing Limitations

Although it’s important to emphasize the significance of your study, you can also use the conclusion to briefly address any limitations you discovered while conducting your research, such as time constraints or a shortage of resources. Doing this demonstrates a balanced and honest approach to your research.

Connecting to the Introduction

In your conclusion, you can circle back to your introduction , perhaps by referring to a quote or anecdote you discussed earlier. If you end your paper on a similar note to how you began it, you will create a sense of cohesion for the reader and remind them of the meaning and significance of your research.

Ending With a Thought-Provoking Statement

Consider ending your paper with a thought-provoking and memorable statement that relates to the impact of your research questions or hypothesis. This statement can be a call to action, a philosophical question, or a prediction for the future (positive or negative). Here’s an example that uses the same topic as above (social media and mental health):

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In a short paper—even a research paper—you don’t need to provide an exhaustive summary as part of your conclusion. But you do need to make some kind of transition between your final body paragraph and your concluding paragraph. This may come in the form of a few sentences of summary. Or it may come in the form of a sentence that brings your readers back to your thesis or main idea and reminds your readers where you began and how far you have traveled.

So, for example, in a paper about the relationship between ADHD and rejection sensitivity, Vanessa Roser begins by introducing readers to the fact that researchers have studied the relationship between the two conditions and then provides her explanation of that relationship. Here’s her thesis: “While socialization may indeed be an important factor in RS, I argue that individuals with ADHD may also possess a neurological predisposition to RS that is exacerbated by the differing executive and emotional regulation characteristic of ADHD.”

In her final paragraph, Roser reminds us of where she started by echoing her thesis: “This literature demonstrates that, as with many other conditions, ADHD and RS share a delicately intertwined pattern of neurological similarities that is rooted in the innate biology of an individual’s mind, a connection that cannot be explained in full by the behavioral mediation hypothesis.”

Highlight the “so what”

At the beginning of your paper, you explain to your readers what’s at stake—why they should care about the argument you’re making. In your conclusion, you can bring readers back to those stakes by reminding them why your argument is important in the first place. You can also draft a few sentences that put those stakes into a new or broader context.

In the conclusion to her paper about ADHD and RS, Roser echoes the stakes she established in her introduction—that research into connections between ADHD and RS has led to contradictory results, raising questions about the “behavioral mediation hypothesis.”

She writes, “as with many other conditions, ADHD and RS share a delicately intertwined pattern of neurological similarities that is rooted in the innate biology of an individual’s mind, a connection that cannot be explained in full by the behavioral mediation hypothesis.”

Leave your readers with the “now what”

After the “what” and the “so what,” you should leave your reader with some final thoughts. If you have written a strong introduction, your readers will know why you have been arguing what you have been arguing—and why they should care. And if you’ve made a good case for your thesis, then your readers should be in a position to see things in a new way, understand new questions, or be ready for something that they weren’t ready for before they read your paper.

In her conclusion, Roser offers two “now what” statements. First, she explains that it is important to recognize that the flawed behavioral mediation hypothesis “seems to place a degree of fault on the individual. It implies that individuals with ADHD must have elicited such frequent or intense rejection by virtue of their inadequate social skills, erasing the possibility that they may simply possess a natural sensitivity to emotion.” She then highlights the broader implications for treatment of people with ADHD, noting that recognizing the actual connection between rejection sensitivity and ADHD “has profound implications for understanding how individuals with ADHD might best be treated in educational settings, by counselors, family, peers, or even society as a whole.”

To find your own “now what” for your essay’s conclusion, try asking yourself these questions:

What can my readers now understand, see in a new light, or grapple with that they would not have understood in the same way before reading my paper? Are we a step closer to understanding a larger phenomenon or to understanding why what was at stake is so important?
What questions can I now raise that would not have made sense at the beginning of my paper? Questions for further research? Other ways that this topic could be approached?
Are there other applications for my research? Could my questions be asked about different data in a different context? Could I use my methods to answer a different question?
What action should be taken in light of this argument? What action do I predict will be taken or could lead to a solution?
What larger context might my argument be a part of?

What to avoid in your conclusion

a complete restatement of all that you have said in your paper.
a substantial counterargument that you do not have space to refute; you should introduce counterarguments before your conclusion.
an apology for what you have not said. If you need to explain the scope of your paper, you should do this sooner—but don’t apologize for what you have not discussed in your paper.
fake transitions like “in conclusion” that are followed by sentences that aren’t actually conclusions. (“In conclusion, I have now demonstrated that my thesis is correct.”)
picture_as_pdf Conclusions

How to Write Conclusion in Research Paper (With Example)

Writing a strong conclusion is a crucial part of any research paper. It provides a final opportunity to summarize your key findings, restate your thesis, and leave a lasting impression on your reader. However, many students struggle with how to effectively write a conclusion that ties everything together.

In this article, we’ll provide some tips and strategies for writing a compelling conclusion, along with an example to help illustrate the process. By following these guidelines, you can ensure that your research paper ends on a high note and leaves a lasting impact on your audience.

Why Conclusion is Important in Research Paper

The conclusion is the final chapter of your research paper journey, sealing the deal on all your hard work. After thoroughly laying out your main points and arguments in the body paragraphs, the conclusion gives you a chance to tie everything together into a neat, cohesive package.

More than just summarizing your key ideas, an effective conclusion shows readers the bigger picture of your research and why it matters. It highlights the significance of your findings , explains how your work contributes to the field, and points to potential future directions stemming from your study.

The conclusion is your last chance to leave a lasting impact and compel readers to seriously consider your perspective. With the right phrasing and tone, you can amplify the power of your work. Choose your words wisely, be persuasive yet diplomatic, and guide readers to walk away feeling satisfied by your reasoning and conclusions.

Approach the conclusion thoughtfully, reflect deeply on the larger meaning of your research, and craft impactful final sentences that linger in the reader’s mind. Wield your conclusion skillfully to make your research paper transformative and memorable. A powerful, thoughtful conclusion inspires action, sparks curiosity, and showcases the valuable insights you bring to the academic conversation.

How to Write Conclusion for a Research Paper

Crafting an effective conclusion in research paper requires thoughtful consideration and deliberate effort. After presenting your findings and analysis, the conclusion allows you to close your work with a flourish.

Begin by briefly summarizing the main points of your paper, provide a quick recap of your thesis, methodology, and key findings without repeating too much details from the body. Use this as an opportunity to reinforce your main argument and position within the field.

Next, highlight the significance and implications of your research. What new insights or perspectives does your work contribute? Discuss how your findings can inform future studies or practical applications. Convey why your research matters and how it moves the needle forward in your discipline.

Address any limitations of the current study and propose potential next steps that could be taken by you or other scholars to further the research. This shows readers you have critically considered ways to continue expanding knowledge in this area.

Finally, close with a memorable statement that captures the essence of your work and leaves a lasting impression. This could be an apt metaphor, a call to action, or a thought provoking question for readers to ponder. Choose words that will resonate with your audience and demonstrate the impact of your research.

With care and creativity, your conclusion can elevate your paper and cement your scholarly authority. Revisit often as you write to ensure your conclusion accomplishes its purpose, to convince readers of the value of your study and ignite further progress in your field.

What Not to Include in a Research Paper Conclusion

1. New Data: In a research paper conclusion, avoid presenting new data or evidence that wasn’t discussed earlier in the paper. It’s the time to summarize, analyze, or explain the significance of data already provided, not to introduce new material.

2. Irrelevant Details: The conclusion is not the spot for extraneous details not directly related to your research or its findings. Be focused and concise, tying up the paper neatly without going off-target.

3. Personal Opinions: Try not to include personal beliefs or subjective opinions unless your paper calls for it. Stick to empirical evidence, facts, and objective interpretation of your research.

4. Vague Summarization: While summarizing is the essence of a conclusion, too much of a broad or vague narrative should be avoided. Your conclusion shouldn’t be a generalization of the research but should specifically state your significant findings and their implications.

5. Overstating Results: No matter how exhilarating your research may be, don’t exaggerate its implications or general applications. Remember to acknowledge limitations or potential areas for future exploration.

6. Procrastinating: Refrain from leaving unresolved issues for future research. The conclusion is meant to tie up loose ends, not create more.

7. Repetition: While some reiteration is necessary, completely repeating the same phrases and points made previously can make your conclusion sound boring and redundant. Instead, try to look at your argument from a fresh, summarized perspective.

8. Apologies: Do not apologize or discredit your research efforts. Avoid phrases like, “This research was only” or “Although the study wasn’t able to prove”. A conclusion should confidently present your research results even if they’re unexpected or differ from your hypothesis.

9. Impractical Recommendations: While it’s often good to suggest directions for future research, don’t go overboard by proposing impractical or unachievable goals. Keep your recommendations relevant to your findings and within the realm of possibility.

10. Too Much Jargon: While it’s appropriate to use technical language throughout your research paper, remember the conclusion might be what a layman reads. Stick with a happy medium of professional lingo intermixed with understandable, plain language.

Also Check: Conclusion for Internship Report

Conclusion in research Example

Research: Impact of Social Media Use on Adolescent Mental Health.

In conclusion, this study has demonstrated the significant impact of social media use on adolescent mental health. Our findings indicate that frequent social media use is associated with higher levels of anxiety and depression, particularly among girls. These results underscore the need for continued research in this area, as well as the development of interventions and strategies to promote healthy social media use among young people. By addressing this issue, we can help to ensure the well-being and success of the next generation.

Conclusion in Research Paper Example

Research: Impact of climate change on coral reefs in Florida.

In conclusion, the effect of climate change on Florida’s coral reefs presents a significant concern for the state’s ecosystem and economy. The data collected during this investigation reveal a direct correlation between rising ocean temperatures and coral bleaching events. This pattern has increased over the past decade, indicating that coral reefs’ health directly correlates with climate change effects.

Example Conclusion in Research

Research: The Influence of Social Media on Consumer Buying Behavior

Social media significantly shapes consumer buying behavior. Its power to influence is seen through peer opinions, online advertising, and brand communication. However, with the potential for misinformation, the reliability and quality of information are areas for further study. Despite these concerns, businesses leveraging social media can effectively boost their market reach and sales.

Research Paper Conclusion

Research: Impacts of Remote Work on Employee Productivity

Remote work has been found to notably enhance employee productivity. The elimination of commuting time, flexible scheduling, and comforting environment contribute to this increase. However, factors like home distractions and technological difficulties offer room for further research. Yet, integrating remote work can be a strategic pathway towards improved efficiency and workforce satisfaction.

These examples demonstrate techniques for crafting an effective conclusion in a research paper, providing your thesis with a powerful final statement. Now it is your turn to compose a strong concluding paragraph that summarizes your findings, reinforces your central argument, and leaves readers with a memorable takeaway.

Remember to restate your thesis without repeating it verbatim, highlight your main points without introducing new evidence, and end on a note that conveys the significance of your research. With a clear structure and purpose, proper grammar, and impactful writing, you can give your paper the persuasive conclusion it deserves.

Writing an effective conclusion takes practice, but by honing these skills you will elevate your academic writing to new heights. Use the strategies outlined here as a guide, believe in your capabilities, and soon you will be adept at concluding research papers powerfully. The final paragraph is your last chance to impress readers, so make it count!

What makes an effective discussion?

When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.

A successful discussion section puts your findings in context. It should include:

the results of your research,
a discussion of related research, and
a comparison between your results and initial hypothesis.

Tip: Not all journals share the same naming conventions.

You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.

Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts.

Questions to ask yourself:

Was my hypothesis correct?
If my hypothesis is partially correct or entirely different, what can be learned from the results?
How do the conclusions reshape or add onto the existing knowledge in the field? What does previous research say about the topic?
Why are the results important or relevant to your audience? Do they add further evidence to a scientific consensus or disprove prior studies?
How can future research build on these observations? What are the key experiments that must be done?
What is the “take-home” message you want your reader to leave with?

How to structure a discussion

Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:

Writing Tips

While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results!

Read the journal’s guidelines on the discussion and conclusion sections. If possible, learn about the guidelines before writing the discussion to ensure you’re writing to meet their expectations.
Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion.
Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and limitations of the research.
State whether the results prove or disprove your hypothesis. If your hypothesis was disproved, what might be the reasons?
Introduce new or expanded ways to think about the research question. Indicate what next steps can be taken to further pursue any unresolved questions.
If dealing with a contemporary or ongoing problem, such as climate change, discuss possible consequences if the problem is avoided.
Be concise. Adding unnecessary detail can distract from the main findings.

Don’t

Rewrite your abstract. Statements with “we investigated” or “we studied” generally do not belong in the discussion.
Include new arguments or evidence not previously discussed. Necessary information and evidence should be introduced in the main body of the paper.
Apologize. Even if your research contains significant limitations, don’t undermine your authority by including statements that doubt your methodology or execution.
Shy away from speaking on limitations or negative results. Including limitations and negative results will give readers a complete understanding of the presented research. Potential limitations include sources of potential bias, threats to internal or external validity, barriers to implementing an intervention and other issues inherent to the study design.
Overstate the importance of your findings. Making grand statements about how a study will fully resolve large questions can lead readers to doubt the success of the research.

Snippets of Effective Discussions:

Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach

Identifying reliable indicators of fitness in polar bears

How to Write a Great Title
How to Write an Abstract
How to Write Your Methods
How to Report Statistics
How to Edit Your Work

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The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

How to write a strong conclusion for your research paper

Last updated

17 February 2024

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Writing a research paper is a chance to share your knowledge and hypothesis. It's an opportunity to demonstrate your many hours of research and prove your ability to write convincingly.

Ideally, by the end of your research paper, you'll have brought your readers on a journey to reach the conclusions you've pre-determined. However, if you don't stick the landing with a good conclusion, you'll risk losing your reader’s trust.

Writing a strong conclusion for your research paper involves a few important steps, including restating the thesis and summing up everything properly.

Find out what to include and what to avoid, so you can effectively demonstrate your understanding of the topic and prove your expertise.

Why is a good conclusion important?

A good conclusion can cement your paper in the reader’s mind. Making a strong impression in your introduction can draw your readers in, but it's the conclusion that will inspire them.

What to include in a research paper conclusion

There are a few specifics you should include in your research paper conclusion. Offer your readers some sense of urgency or consequence by pointing out why they should care about the topic you have covered. Discuss any common problems associated with your topic and provide suggestions as to how these problems can be solved or addressed.

The conclusion should include a restatement of your initial thesis. Thesis statements are strengthened after you’ve presented supporting evidence (as you will have done in the paper), so make a point to reintroduce it at the end.

Finally, recap the main points of your research paper, highlighting the key takeaways you want readers to remember. If you've made multiple points throughout the paper, refer to the ones with the strongest supporting evidence.

Steps for writing a research paper conclusion

Many writers find the conclusion the most challenging part of any research project . By following these three steps, you'll be prepared to write a conclusion that is effective and concise.

Step 1: Restate the problem

Always begin by restating the research problem in the conclusion of a research paper. This serves to remind the reader of your hypothesis and refresh them on the main point of the paper.

When restating the problem, take care to avoid using exactly the same words you employed earlier in the paper.

Step 2: Sum up the paper

After you've restated the problem, sum up the paper by revealing your overall findings. The method for this differs slightly, depending on whether you're crafting an argumentative paper or an empirical paper.

Argumentative paper: Restate your thesis and arguments

Argumentative papers involve introducing a thesis statement early on. In crafting the conclusion for an argumentative paper, always restate the thesis, outlining the way you've developed it throughout the entire paper.

It might be appropriate to mention any counterarguments in the conclusion, so you can demonstrate how your thesis is correct or how the data best supports your main points.

Empirical paper: Summarize research findings

Empirical papers break down a series of research questions. In your conclusion, discuss the findings your research revealed, including any information that surprised you.

Be clear about the conclusions you reached, and explain whether or not you expected to arrive at these particular ones.

Step 3: Discuss the implications of your research

Argumentative papers and empirical papers also differ in this part of a research paper conclusion. Here are some tips on crafting conclusions for argumentative and empirical papers.

Argumentative paper: Powerful closing statement

In an argumentative paper, you'll have spent a great deal of time expressing the opinions you formed after doing a significant amount of research. Make a strong closing statement in your argumentative paper's conclusion to share the significance of your work.

You can outline the next steps through a bold call to action, or restate how powerful your ideas turned out to be.

Empirical paper: Directions for future research

Empirical papers are broader in scope. They usually cover a variety of aspects and can include several points of view.

To write a good conclusion for an empirical paper, suggest the type of research that could be done in the future, including methods for further investigation or outlining ways other researchers might proceed.

If you feel your research had any limitations, even if they were outside your control, you could mention these in your conclusion.

After you finish outlining your conclusion, ask someone to read it and offer feedback. In any research project you're especially close to, it can be hard to identify problem areas. Having a close friend or someone whose opinion you value read the research paper and provide honest feedback can be invaluable. Take note of any suggested edits and consider incorporating them into your paper if they make sense.

Things to avoid in a research paper conclusion

Keep these aspects to avoid in mind as you're writing your conclusion and refer to them after you've created an outline.

Dry summary

Writing a memorable, succinct conclusion is arguably more important than a strong introduction. Take care to avoid just rephrasing your main points, and don't fall into the trap of repeating dry facts or citations.

You can provide a new perspective for your readers to think about or contextualize your research. Either way, make the conclusion vibrant and interesting, rather than a rote recitation of your research paper’s highlights.

Clichéd or generic phrasing

Your research paper conclusion should feel fresh and inspiring. Avoid generic phrases like "to sum up" or "in conclusion." These phrases tend to be overused, especially in an academic context and might turn your readers off.

The conclusion also isn't the time to introduce colloquial phrases or informal language. Retain a professional, confident tone consistent throughout your paper’s conclusion so it feels exciting and bold.

New data or evidence

While you should present strong data throughout your paper, the conclusion isn't the place to introduce new evidence. This is because readers are engaged in actively learning as they read through the body of your paper.

By the time they reach the conclusion, they will have formed an opinion one way or the other (hopefully in your favor!). Introducing new evidence in the conclusion will only serve to surprise or frustrate your reader.

Ignoring contradictory evidence

If your research reveals contradictory evidence, don't ignore it in the conclusion. This will damage your credibility as an expert and might even serve to highlight the contradictions.

Be as transparent as possible and admit to any shortcomings in your research, but don't dwell on them for too long.

Ambiguous or unclear resolutions

The point of a research paper conclusion is to provide closure and bring all your ideas together. You should wrap up any arguments you introduced in the paper and tie up any loose ends, while demonstrating why your research and data are strong.

Use direct language in your conclusion and avoid ambiguity. Even if some of the data and sources you cite are inconclusive or contradictory, note this in your conclusion to come across as confident and trustworthy.

Examples of research paper conclusions

Your research paper should provide a compelling close to the paper as a whole, highlighting your research and hard work. While the conclusion should represent your unique style, these examples offer a starting point:

Ultimately, the data we examined all point to the same conclusion: Encouraging a good work-life balance improves employee productivity and benefits the company overall. The research suggests that when employees feel their personal lives are valued and respected by their employers, they are more likely to be productive when at work. In addition, company turnover tends to be reduced when employees have a balance between their personal and professional lives. While additional research is required to establish ways companies can support employees in creating a stronger work-life balance, it's clear the need is there.

Social media is a primary method of communication among young people. As we've seen in the data presented, most young people in high school use a variety of social media applications at least every hour, including Instagram and Facebook. While social media is an avenue for connection with peers, research increasingly suggests that social media use correlates with body image issues. Young girls with lower self-esteem tend to use social media more often than those who don't log onto social media apps every day. As new applications continue to gain popularity, and as more high school students are given smartphones, more research will be required to measure the effects of prolonged social media use.

What are the different kinds of research paper conclusions?

There are no formal types of research paper conclusions. Ultimately, the conclusion depends on the outline of your paper and the type of research you’re presenting. While some experts note that research papers can end with a new perspective or commentary, most papers should conclude with a combination of both. The most important aspect of a good research paper conclusion is that it accurately represents the body of the paper.

Can I present new arguments in my research paper conclusion?

Research paper conclusions are not the place to introduce new data or arguments. The body of your paper is where you should share research and insights, where the reader is actively absorbing the content. By the time a reader reaches the conclusion of the research paper, they should have formed their opinion. Introducing new arguments in the conclusion can take a reader by surprise, and not in a positive way. It might also serve to frustrate readers.

How long should a research paper conclusion be?

There's no set length for a research paper conclusion. However, it's a good idea not to run on too long, since conclusions are supposed to be succinct. A good rule of thumb is to keep your conclusion around 5 to 10 percent of the paper's total length. If your paper is 10 pages, try to keep your conclusion under one page.

What should I include in a research paper conclusion?

A good research paper conclusion should always include a sense of urgency, so the reader can see how and why the topic should matter to them. You can also note some recommended actions to help fix the problem and some obstacles they might encounter. A conclusion should also remind the reader of the thesis statement, along with the main points you covered in the paper. At the end of the conclusion, add a powerful closing statement that helps cement the paper in the mind of the reader.

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Writing a Research Paper Conclusion - Step-by-Step Guide

What is a Research Paper Conclusion?

A research paper conclusion is like the final chapter of your paper. It's where you bring everything together and leave a lasting impression on your readers.

In simple terms, it's the last part where you sum up what you found during your research and explain why it matters.

The conclusion isn't just a summary; it's a chance to make your research memorable and show its importance.

Types of Research Paper Conclusions

When it comes to writing the conclusion of your research paper, there isn't a one-size-fits-all approach. Different types of research papers call for different types of conclusions. Here are some common types:

Summarizing Conclusion

This type recaps the key points and findings of your research. It's like giving your readers a quick overview of what you discovered without introducing new information. Summarizing conclusions works well for straightforward research papers.

Reflective Conclusion

A reflective conclusion allows you to share your personal thoughts on the research process, challenges faced, and lessons learned. It adds a human touch to your paper, giving readers insight into your journey as a researcher.

Open-ended Conclusion

Some research papers benefit from an open-ended conclusion that leaves room for further exploration. This type invites readers to think critically, ask questions, or even conduct additional research on the same topic.

How to Write a Research Paper Conclusion: 7 Steps

Writing an effective conclusion for your research paper involves more than just summarizing your findings. Follow these six essential steps to ensure your conclusion leaves a lasting impact:

Step 1: Restate the Research Problem

Start wrapping up your paper by going back to the main research question or issue you were investigating.

Remind your readers about what you were trying to find out or understand. This gives your conclusion a clear connection to the original goal of your research, helping readers see the bigger picture.

Step 2: Revisit Your Thesis Statement

Go back to the main idea or argument you had in your paper—this is called your thesis statement. Double-check that your conclusion matches and supports what you wanted to prove or talk about in the beginning.

This step is important because it keeps your conclusion connected to the main point of your research, making everything fit together nicely.

Step 3: Summarize Key Points

Give a short and clear recap of the most important things you found in your research. Keep it simple and stick to what you've already talked about—don't bring in new details now.

The goal is to remind your readers of the important stuff you covered earlier. This helps to underline why your research is important and what you want them to take away from it.

Step 4: Discuss the Implications

Address the broader implications of your research. Explain why your findings matter and how they contribute to the existing body of knowledge in your field.

Discuss the practical applications of your research and highlight any potential areas for further exploration.

Step 5: Connect with the Introduction

Create a seamless connection between your conclusion and the introduction. Referencing key elements from the introduction helps to create a cohesive narrative for your paper.

This connection gives your research a sense of completeness and unity.

Step 6: Consider the "So What?" Factor

Ask yourself the question, "So what?" Why should readers care about your research? Clearly articulate the significance of your findings and their relevance to the broader academic or real-world context.

Demonstrating the impact of your research adds depth to your conclusion.

Step 7: End with a Strong Closing Statement:

Conclude your research paper with a memorable closing statement. This could be a thought-provoking reflection, a call to action, or a suggestion for future research.

A strong closing leaves a lasting impression on your readers and emphasizes the importance of your work.

Research Paper Conclusion Examples

When it comes to writing a conclusion for your research paper, examining examples can offer valuable insights. Let’s take a look at this comprehensive example given below:

Still wondering how to write the conclusion for your research paper? Check out these examples for better understanding:

Conclusion For A Research Paper APA

Conclusion For A Research Paper Example Pdf

Conclusion For A Research Paper Pdf

Conclusion For A Research Paper Middle School

Conclusion For A Scientific Paper

Conclusion For A Research Paper Sample

Things to Avoid While Writing the Research Paper Conclusion

While crafting a conclusion for your research paper, it's crucial to steer clear of common pitfalls that can diminish the impact of your final remarks.

Here are some things to avoid:

Repetition: Avoid rehashing the exact language used in the introduction or body of your paper. A conclusion should summarize key points without duplicating content.
Introducing New Information: Resist the temptation to introduce new ideas or data in the conclusion. This section is for summarizing existing content and reinforcing key findings.
Overly Complex Language: Keep your conclusion clear and accessible. Avoid introducing overly complex or technical language that might confuse your readers.
Lack of Connection to Introduction: Ensure that your conclusion ties back to the introduction. Failing to connect these sections can make your paper feel disjointed.
Vague Statements: Steer clear of vague statements that lack substance. Clearly articulate the significance of your findings and their broader implications.
Apologies or Excuses: Avoid including apologies or excuses for limitations in your research. While acknowledging limitations is important, the conclusion is not the place to dwell on them.
New Arguments or Debates: The conclusion is not the space to introduce new debates or arguments. Keep the focus on summarizing your research and its implications.
Abrupt Endings: A conclusion should not end abruptly. Instead, provide a thoughtful and well-rounded closing statement about the results of your study.

To sum it up, we've gone through important steps to make your research paper conclusion strong. We covered things like going back to your main question, talking about the most important points, and thinking about why your research matters in the real world.

Remember, a good ending is more than just a summary; it captures the heart of your research and answers the big "So what?" question.

Remember, don't say the same things too much, don't add new details at the end, and keep your language simple!

If you ever need help with your academic writing, MyPerfectWords.com is here for you. Our expert writers are committed to helping you excel in your research papers and beyond.

Take the next step towards academic success with MyPerfectWords.com, and hire our essay writing service today!

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Dr. Barbara is a highly experienced writer and author who holds a Ph.D. degree in public health from an Ivy League school. She has worked in the medical field for many years, conducting extensive research on various health topics. Her writing has been featured in several top-tier publications.

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How to Write a Conclusion for a Research Paper

Last Updated: June 29, 2023 Approved

This article was co-authored by Christopher Taylor, PhD . Christopher Taylor is an Adjunct Assistant Professor of English at Austin Community College in Texas. He received his PhD in English Literature and Medieval Studies from the University of Texas at Austin in 2014. wikiHow marks an article as reader-approved once it receives enough positive feedback. This article received 42 testimonials and 82% of readers who voted found it helpful, earning it our reader-approved status. This article has been viewed 2,256,771 times.

The conclusion of a research paper needs to summarize the content and purpose of the paper without seeming too wooden or dry. Every basic conclusion must share several key elements, but there are also several tactics you can play around with to craft a more effective conclusion and several you should avoid to prevent yourself from weakening your paper's conclusion. Here are some writing tips to keep in mind when creating a conclusion for your next research paper.

Sample Conclusions

Writing a basic conclusion.

Do not spend a great amount of time or space restating your topic.
A good research paper will make the importance of your topic apparent, so you do not need to write an elaborate defense of your topic in the conclusion.
Usually a single sentence is all you need to restate your topic.
An example would be if you were writing a paper on the epidemiology of infectious disease, you might say something like "Tuberculosis is a widespread infectious disease that affects millions of people worldwide every year."
Yet another example from the humanities would be a paper about the Italian Renaissance: "The Italian Renaissance was an explosion of art and ideas centered around artists, writers, and thinkers in Florence."

A thesis is a narrowed, focused view on the topic at hand.
This statement should be rephrased from the thesis you included in your introduction. It should not be identical or too similar to the sentence you originally used.
Try re-wording your thesis statement in a way that complements your summary of the topic of your paper in your first sentence of your conclusion.
An example of a good thesis statement, going back to the paper on tuberculosis, would be "Tuberculosis is a widespread disease that affects millions of people worldwide every year. Due to the alarming rate of the spread of tuberculosis, particularly in poor countries, medical professionals are implementing new strategies for the diagnosis, treatment, and containment of this disease ."

Step 3 Briefly summarize your main points.

A good way to go about this is to re-read the topic sentence of each major paragraph or section in the body of your paper.
Find a way to briefly restate each point mentioned in each topic sentence in your conclusion. Do not repeat any of the supporting details used within your body paragraphs.
Under most circumstances, you should avoid writing new information in your conclusion. This is especially true if the information is vital to the argument or research presented in your paper.
For example, in the TB paper you could summarize the information. "Tuberculosis is a widespread disease that affects millions of people worldwide. Due to the alarming rate of the spread of tuberculosis, particularly in poor countries, medical professionals are implementing new strategies for the diagnosis, treatment, and containment of this disease. In developing countries, such as those in Africa and Southeast Asia, the rate of TB infections is soaring. Crowded conditions, poor sanitation, and lack of access to medical care are all compounding factors in the spread of the disease. Medical experts, such as those from the World Health Organization are now starting campaigns to go into communities in developing countries and provide diagnostic testing and treatments. However, the treatments for TB are very harsh and have many side effects. This leads to patient non-compliance and spread of multi-drug resistant strains of the disease."

Note that this is not needed for all research papers.
If you already fully explained what the points in your paper mean or why they are significant, you do not need to go into them in much detail in your conclusion. Simply restating your thesis or the significance of your topic should suffice.
It is always best practice to address important issues and fully explain your points in the body of your paper. The point of a conclusion to a research paper is to summarize your argument for the reader and, perhaps, to call the reader to action if needed.

Step 5 Make a call to action when appropriate.

Note that a call for action is not essential to all conclusions. A research paper on literary criticism, for instance, is less likely to need a call for action than a paper on the effect that television has on toddlers and young children.
A paper that is more likely to call readers to action is one that addresses a public or scientific need. Let's go back to our example of tuberculosis. This is a very serious disease that is spreading quickly and with antibiotic-resistant forms.
A call to action in this research paper would be a follow-up statement that might be along the lines of "Despite new efforts to diagnose and contain the disease, more research is needed to develop new antibiotics that will treat the most resistant strains of tuberculosis and ease the side effects of current treatments."

For example, if you are writing a history paper, then you might discuss how the historical topic you discussed matters today. If you are writing about a foreign country, then you might use the conclusion to discuss how the information you shared may help readers understand their own country.

Making Your Conclusion as Effective as Possible

Step 1 Stick with a basic synthesis of information.

Since this sort of conclusion is so basic, you must aim to synthesize the information rather than merely summarizing it.
Instead of merely repeating things you already said, rephrase your thesis and supporting points in a way that ties them all together.
By doing so, you make your research paper seem like a "complete thought" rather than a collection of random and vaguely related ideas.

Ask a question in your introduction. In your conclusion, restate the question and provide a direct answer.
Write an anecdote or story in your introduction but do not share the ending. Instead, write the conclusion to the anecdote in the conclusion of your paper.
For example, if you wanted to get more creative and put a more humanistic spin on a paper on tuberculosis, you might start your introduction with a story about a person with the disease, and refer to that story in your conclusion. For example, you could say something like this before you re-state your thesis in your conclusion: "Patient X was unable to complete the treatment for tuberculosis due to severe side effects and unfortunately succumbed to the disease."
Use the same concepts and images introduced in your introduction in your conclusion. The images may or may not appear at other points throughout the research paper.

Include enough information about your topic to back the statement up but do not get too carried away with excess detail.
If your research did not provide you with a clear-cut answer to a question posed in your thesis, do not be afraid to indicate as much.
Restate your initial hypothesis and indicate whether you still believe it or if the research you performed has begun swaying your opinion.
Indicate that an answer may still exist and that further research could shed more light on the topic at hand.

This may not be appropriate for all types of research papers. Most research papers, such as one on effective treatment for diseases, will have the information to make the case for a particular argument already in the paper.
A good example of a paper that might ask a question of the reader in the ending is one about a social issue, such as poverty or government policy.
Ask a question that will directly get at the heart or purpose of the paper. This question is often the same question, or some version of it, that you may have started with when you began your research.
Make sure that the question can be answered by the evidence presented in your paper.
If desired you can briefly summarize the answer after stating the question. You could also leave the question hanging for the reader to answer, though.

Even without a call to action, you can still make a recommendation to your reader.
For instance, if you are writing about a topic like third-world poverty, you can various ways for the reader to assist in the problem without necessarily calling for more research.
Another example would be, in a paper about treatment for drug-resistant tuberculosis, you could suggest donating to the World Health Organization or research foundations that are developing new treatments for the disease.

Avoiding Common Pitfalls

These sayings usually sound stiff, unnatural, or trite when used in writing.
Moreover, using a phrase like "in conclusion" to begin your conclusion is a little too straightforward and tends to lead to a weak conclusion. A strong conclusion can stand on its own without being labeled as such.

Step 2 Do not wait until the conclusion to state your thesis.

Always state the main argument or thesis in the introduction. A research paper is an analytical discussion of an academic topic, not a mystery novel.
A good, effective research paper will allow your reader to follow your main argument from start to finish.
This is why it is best practice to start your paper with an introduction that states your main argument and to end the paper with a conclusion that re-states your thesis for re-iteration.

All significant information should be introduced in the body of the paper.
Supporting evidence expands the topic of your paper by making it appear more detailed. A conclusion should narrow the topic to a more general point.
A conclusion should only summarize what you have already stated in the body of your paper.
You may suggest further research or a call to action, but you should not bring in any new evidence or facts in the conclusion.

Step 4 Avoid changing the tone of the paper.

Most often, a shift in tone occurs when a research paper with an academic tone gives an emotional or sentimental conclusion.
Even if the topic of the paper is of personal significance for you, you should not indicate as much in your paper.
If you want to give your paper a more humanistic slant, you could start and end your paper with a story or anecdote that would give your topic more personal meaning to the reader.
This tone should be consistent throughout the paper, however.

Apologetic statements include phrases like "I may not be an expert" or "This is only my opinion."
Statements like this can usually be avoided by refraining from writing in the first-person.
Avoid any statements in the first-person. First-person is generally considered to be informal and does not fit with the formal tone of a research paper.

Community Q&A

↑ http://owl.english.purdue.edu/owl/resource/724/04/
↑ http://www.crlsresearchguide.org/18_Writing_Conclusion.asp
↑ http://writing.wisc.edu/Handbook/PlanResearchPaper.html#conclusion
↑ http://writingcenter.unc.edu/handouts/conclusions/
↑ http://writing2.richmond.edu/writing/wweb/conclude.html

About This Article

To write a conclusion for a research paper, start by restating your thesis statement to remind your readers what your main topic is and bring everything full circle. Then, briefly summarize all of the main points you made throughout your paper, which will help remind your readers of everything they learned. You might also want to include a call to action if you think more research or work needs to be done on your topic by writing something like, "Despite efforts to contain the disease, more research is needed to develop antibiotics." Finally, end your conclusion by explaining the broader context of your topic and why your readers should care about it, which will help them understand why your topic is relevant and important. For tips from our Academic co-author, like how to avoid common pitfalls when writing your conclusion, scroll down! Did this summary help you? Yes No

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How to Write a Conclusion for a Research Paper

Writing a conclusion for a research paper is a critical step that often determines the overall impact and impression the paper leaves on the reader. While some may view the conclusion as a mere formality, it is actually an opportunity to wrap up the main points, provide closure, and leave a lasting impression. In this article, we will explore the importance of a well-crafted conclusion and discuss various tips and strategies to help you write an engaging and impactful conclusion for your research paper.

Introduction

Before delving into the specifics of writing a conclusion, it is important to understand why it is such a crucial component of a research paper. The conclusion serves to summarize the main points of the paper and reemphasize their significance. A well-written conclusion can leave the reader satisfied and inspired, while a poorly executed one may undermine the credibility of the entire paper. Therefore, it is essential to give careful thought and attention to crafting an effective conclusion.

When writing a research paper, the conclusion acts as the final destination for the reader. It is the point where all the information, arguments, and evidence presented throughout the paper converge. Just as a traveler reaches the end of a journey, the reader reaches the conclusion to find closure and a sense of fulfillment. This is why the conclusion should not be taken lightly; it is a critical opportunity to leave a lasting impact on the reader.

Moreover, the conclusion is not merely a repetition of the introduction or a summary of the main points. It goes beyond that by providing a deeper understanding of the research findings and their implications. It allows the writer to reflect on the significance of their work and its potential contributions to the field. By doing so, the conclusion elevates the research paper from a mere collection of facts to a thought-provoking piece of scholarship.

In the following sections, we will explore various strategies and techniques for crafting a compelling conclusion. By understanding the importance of the conclusion and learning how to write one effectively, you will be equipped to create impactful research papers.

Structuring the Conclusion

In order to create an effective conclusion, it is important to consider its structure. A well-structured conclusion should begin by restating the thesis statement and summarizing the main points of the paper. It should then move on to provide a concise synthesis of the key findings and arguments, highlighting their implications and relevance. Finally, the conclusion should end with a thought-provoking statement that leaves the reader with a lasting impression.

Additionally, using phrases like "this research demonstrates," "the findings show," or "it is clear that" can help to highlight the significance of your research and emphasize your main conclusions.

Tips for Writing an Engaging Conclusion

Writing an engaging conclusion requires careful consideration and attention to detail. Here are some tips to help you create an impactful conclusion for your research paper:

Revisit the Introduction: Start your conclusion by referencing your introduction. Remind the reader of the research question or problem you initially posed and show how your research has addressed it.
Summarize Your Main Points: Provide a concise summary of the main points and arguments presented in your paper. Be sure to restate your thesis statement and highlight the key findings.
Offer a Fresh Perspective: Use the conclusion as an opportunity to provide a fresh perspective or offer insights that go beyond the main body of the paper. This will leave the reader with something new to consider.
Leave a Lasting Impression: End your conclusion with a thought-provoking statement or a call to action. This will leave a lasting impression on the reader and encourage further exploration of the research topic.

Addressing Counter Arguments In Conclusion

While crafting your conclusion, you can address any potential counterarguments or limitations of your research. This will demonstrate that you have considered alternative perspectives and have taken them into account in your conclusions. By acknowledging potential counterarguments, you can strengthen the credibility and validity of your research. And by openly discussing limitations, you demonstrate transparency and honesty in your research process.

Language and Tone To Be Used In Conclusion

The language and tone of your conclusion play a crucial role in shaping the overall impression of your research paper. It is important to use clear and concise language that is appropriate for the academic context. Avoid using overly informal or colloquial language that may undermine the credibility of your research. Additionally, consider the tone of your conclusion – it should be professional, confident, and persuasive, while still maintaining a respectful and objective tone.

When it comes to the language used in your conclusion, precision is key. You want to ensure that your ideas are communicated effectively and that there is no room for misinterpretation. Using clear and concise language will not only make your conclusion easier to understand but will also demonstrate your command of the subject matter.

Furthermore, it is important to strike the right balance between formality and accessibility. While academic writing typically requires a more formal tone, you should still aim to make your conclusion accessible to a wider audience. This means avoiding jargon or technical terms that may confuse readers who are not familiar with the subject matter. Instead, opt for language that is clear and straightforward, allowing anyone to grasp the main points of your research.

Another aspect to consider is the tone of your conclusion. The tone should reflect the confidence you have in your research findings and the strength of your argument. By adopting a professional and confident tone, you are more likely to convince your readers of the validity and importance of your research. However, it is crucial to strike a balance and avoid sounding arrogant or dismissive of opposing viewpoints. Maintaining a respectful and objective tone will help you engage with your audience in a more persuasive manner.

Moreover, the tone of your conclusion should align with the overall tone of your research paper. Consistency in tone throughout your paper will create a cohesive and unified piece of writing.

Common Mistakes to Avoid While Writing a Conclusion

When writing a conclusion, there are several common mistakes that researchers often make. By being aware of these pitfalls, you can avoid them and create a more effective conclusion for your research paper. Some common mistakes include:

Repeating the Introduction: A conclusion should not simply be a reworded version of the introduction. While it is important to revisit the main points, try to present them in a fresh and broader perspective, by foregrounding the implications/impacts of your research.
Introducing New Information: The conclusion should not introduce any new information or arguments. Instead, it should focus on summarizing and synthesizing the main points presented in the paper.
Being Vague or General: Avoid using vague or general statements in your conclusion. Instead, be specific and provide concrete examples or evidence to support your main points.
Ending Abruptly: A conclusion should provide a sense of closure and completeness. Avoid ending your conclusion abruptly or leaving the reader with unanswered questions.

Editing and Revising the Conclusion

Just like the rest of your research paper, the conclusion should go through a thorough editing and revising process. This will help to ensure clarity, coherence, and impact in the conclusion. As you revise your conclusion, consider the following:

Check for Consistency: Ensure that your conclusion aligns with the main body of the paper and does not introduce any new or contradictory information.
Eliminate Redundancy: Remove any repetitive or redundant information in your conclusion. Instead, focus on presenting the key points in a concise and engaging manner.
Proofread for Clarity: Read your conclusion aloud or ask someone else to read it to ensure that it is clear and understandable. Check for any grammatical or spelling errors that may distract the reader.
Seek Feedback: Consider sharing your conclusion with peers or mentors to get their feedback and insights. This can help you strengthen your conclusion and make it more impactful.

How to Write Conclusion as a Call to Action

Finally, consider using your conclusion as a call to action. Encourage the reader to take further action, such as conducting additional research or considering the implications of your findings. By providing a clear call to action, you can inspire the reader to actively engage with your research and continue the conversation on the topic.

Adapting to Different Research Paper Types

It is important to adapt your conclusion approach based on the type of research paper you are writing. Different research paper types may require different strategies and approaches to writing the conclusion. For example, a scientific research paper may focus more on summarizing the key findings and implications, while a persuasive research paper may emphasize the call to action and the potential impact of the research. Tailor your conclusion to suit the specific goals and requirements of your research paper.

Final Thoughts

A well-crafted conclusion can leave a lasting impression on the reader and enhance the impact of your research. By following the tips and strategies outlined in this article, you can create an engaging and impactful conclusion that effectively summarizes your main points, addresses potential counterarguments, and leaves the reader with a sense of closure and inspiration. Embrace the importance of the conclusion and view it as an opportunity to showcase the significance and relevance of your research.

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How to Write a Conclusion for a Research Paper

Posted on May 12, 2023

The key to an impactful research paper is crafting an effective conclusion. The conclusion provides a final opportunity to make a lasting impression on the reader by providing a powerful summary of the main argument and key findings.

A well-written conclusion not only summarizes your research but also ties everything back to your thesis statement. Plus, it provides important takeaways for your reader, highlighting what they should remember from your research and how it contributes to the larger academic discourse.

Crafting an impactful conclusion can be tricky, especially in argumentative papers. However, with our expert tips and tricks, you can rest assured that your conclusion will effectively restate the main argument and thesis statement in a way that resonates with your audience and elevates your research to new heights.

Why is a Conclusion Necessary for a Research Paper?

The conclusion of a research paper is essential in tying together the different parts of the paper and offering a final perspective on the topic. It reinforces the main idea or argument presented and summarizes the key points and findings of the research, highlighting its significance.

Additionally, the conclusion creates a full circle of the research by connecting back to the thesis statement presented at the paper’s beginning. It provides an opportunity to showcase the writer’s critical thinking skills by demonstrating how the research supports the main argument.

The conclusion is essential for a research paper because it provides closure for the reader. It serves as a final destination that helps the reader understand how all the different pieces of information fit together to support the main argument presented. It also offers insights into how the research can inform future studies and contribute to the larger academic discourse.

It also ensures that the reader does not get lost in the vast amount of information presented in the paper by providing a concise and coherent summary of the entire research. Additionally, it helps the reader identify the paper’s main takeaway and understand how the research contributes to the larger body of knowledge in the field.

Leave a Lasting Impression

A well-crafted conclusion is an essential element of any research paper. Its purpose is to leave a lasting impression on the reader and tie together the different parts of the paper.

To achieve this goal, a conclusion should summarize the main points and highlight the key findings of the research. By doing so, the reader can easily understand the focus and significance of the study.

A strong conclusion should also discuss any important findings that can be applied in the real world. This practical perspective gives readers a better sense of the impact and relevance of the research.

Summarize Your Thoughts

The conclusion of a research paper should be concise and provide a summary of the writer’s thoughts and ideas about the research.

It should go beyond simply restating the main points and findings and address the “so what” of the research by explaining how it contributes to the existing body of knowledge on the same topic. This way, the conclusion can give readers a better understanding of the research’s significance and relevance to the broader academic community.

Demonstrate How Important Your Idea Is

Moving beyond a superficial overview and delving into the research in-depth is crucial to create a compelling conclusion. This entails summarizing the key findings of the study, highlighting its main contributions to the field, and placing the results in a broader context. Additionally, it would help if you comprehensively analyzed your work and its implications, underscoring its value to the broader academic community.

New Insights

The conclusion section of a research paper offers an opportunity for the writer to present new insights and approaches to addressing the research problem.

Whether the research outcome is positive or negative, the conclusion provides a platform to discuss practical implications beyond the scope of the research paper. This discussion can help readers understand the potential impact of the research on the broader field and its significance for future research endeavors.

How to Write a Killer Conclusion with Key Points

When writing a conclusion for a research paper, it is important to cover several key points to create a solid and effective conclusion.

Restate the Thesis

When crafting a conclusion, restating the thesis statement is an important step that reminds readers of the research paper’s central focus. However, it should not be a verbatim repetition of the introduction.

By restating the thesis concisely and clearly, you can effectively tie together the main ideas discussed in the body of the paper and emphasize the significance of the research question. However, keep in mind that the restated thesis should capture the essence of the paper and leave the reader with a clear understanding of the main topic and its importance.

Summarize the Main Points

To write an impactful conclusion, summarizing the main points discussed in the body of the paper is essential. This final section provides the writer with a last opportunity to highlight the significance of their research findings.

However, it is equally important to avoid reiterating information already discussed in the body of the paper. Instead, you should synthesize and summarize the most significant points to emphasize the key findings. By doing so, the conclusion can effectively tie together the research findings and provide a clear understanding of the importance of the research topic.

Discuss the Results or Findings

The next step is to discuss the results or findings of the research. The discussion of the results or findings should not simply be a repetition of the information presented in the body of the paper.

Instead, it should provide a more in-depth analysis of the significance of the findings. This can involve explaining why the findings are important, what they mean in the context of the research question, and how they contribute to the field or area of study.

Additionally, it’s crucial to address any limitations or weaknesses of the study in this section. This can provide a more balanced and nuanced understanding of the research and its implications. By doing so, the reader will have a better understanding of the scope and context of the study, which can ultimately enhance the credibility and validity of the research.

Ruminate on Your Thoughts

The final step to crafting an effective conclusion is to ruminate on your thoughts. This provides an opportunity to reflect on the meaning of the research and leaves the reader with something to ponder. Remember, the concluding paragraph should not introduce new information but rather summarize and reflect on the critical points made in the paper.

Furthermore, the conclusion should be integrated into the paper rather than presented as a separate section. It should provide a concise overview of the main findings and suggest avenues for further research.

Different Types of Conclusions

There are various types of conclusions that can be employed to conclude a research paper effectively, depending on the research questions and topic being investigated.

Summarizing

Summarizing conclusions are frequently used to wrap up a research paper effectively. They restate the thesis statement and provide a brief overview of the main findings and outcomes of the research. This type of conclusion serves as a reminder to the reader of the key points discussed throughout the paper and emphasizes the significance of the research topic.

To be effective, summarizing conclusions should be concise and to the point, avoiding any new information not previously discussed in the body of the paper. Moreover, they are particularly useful when there is a clear and direct answer to the research question. This allows you to summarize your findings succinctly and leave the reader with a clear understanding of the implications of the research.

Externalizing

On the opposite end of the spectrum are externalizing conclusions. Unlike summarizing conclusions, externalizing conclusions introduce new ideas that may not be directly related to the research findings. This type of conclusion can be beneficial because it broadens the scope of the research topic and can lead to new insights and directions for future research.

By presenting new ideas, externalizing conclusions can challenge conventional thinking in the field and open up new avenues for exploration. This approach is instrumental in fields where research is ongoing, and new ideas and approaches are constantly being developed.

Editorial conclusions are a type of conclusion that allows the writer to express their commentary on the research findings. They can be particularly effective in connecting the writer’s insights with the research conducted and can offer a unique perspective on the research topic. Adding a personal touch to the conclusion can help engage the reader and leave a lasting impression.

Remember that regardless of the type of conclusion you choose, it should always start with a clear and concise restatement of the thesis statement, followed by a summary of the main findings in the body paragraphs. The first sentence of the conclusion should be impactful and attention-grabbing to make a strong impression on the reader.

What to Avoid in Your Conclusion

When crafting your conclusion, it’s essential to keep in mind several key points to ensure that it is effective and well-received by your audience:

Avoid introducing new ideas or topics that have not been covered in the body of your paper.
Refrain from simply restating what has already been said in your paper without adding new insights or analysis.
Do not apologize for any shortcomings or limitations of your research, as this can undermine the importance of your findings.
Avoid using overly emotional or flowery language, as it can detract from the professionalism and objectivity of the research.
Lastly, avoid any examples of plagiarism. Be sure to properly cite any sources you have used in your research and writing.

Example of a Bad Conclusion

Recapitulation without Insight: In conclusion, this paper has discussed the importance of exercise for physical and mental health. We hope this paper has been helpful to you and encourages you to start exercising today.
Introduction of New Ideas: In conclusion, we have discussed the benefits of exercise and how it can improve physical and mental health. Additionally, we have highlighted the benefits of a plant-based diet and the importance of getting enough sleep for overall well-being.
Emotional Language: In conclusion, exercise is good for your body and mind, and you should definitely start working out today!

Example of a Good Conclusion

Insights and Implications: In light of our investigation, it is evident that regular exercise is undeniably beneficial for both physical and mental well-being, especially if performed at an appropriate duration and frequency. These findings hold significant implications for public health policies and personal wellness decisions.
Limitations and Future Directions: While our investigation has shed light on the benefits of exercise, our study is not without limitations. Future research can delve deeper into the long-term effects of exercise on mental health and explore the impact of exercise on specific populations, such as older adults or individuals with chronic health conditions.
Call to Action: In conclusion, we urge individuals to prioritize exercise as a critical component of their daily routine. By making exercise a habit, we can reap the many benefits of a healthy and active lifestyle.

Final Thoughts

When writing a research paper, the conclusion is one of the most crucial elements to leave a lasting impression on the reader. It should effectively summarize the research and provide valuable insights, leaving the reader with something to ponder.

To accomplish this, it is essential to include vital elements, such as restating the thesis , summarizing the main points, and discussing the findings. However, it is equally important to avoid common mistakes that can undermine the effectiveness of the conclusion, such as introducing new information or repeating the introduction.

So to ensure that your research is of the highest quality, it’s crucial to use proper citations and conduct a thorough literature review. Additionally, it is crucial to proofread the work to eliminate any errors.

Fortunately, there are many available resources to help you with both writing and plagiarism prevention. Quetext , for example, offers a plagiarism checker, citation assistance, and proofreading tools to ensure the writing is top-notch. By incorporating these tips and using available resources, you can create a compelling and memorable conclusion for readers.

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How to conclude an essay | Interactive example

How to Conclude an Essay | Interactive Example

Published on January 24, 2019 by Shona McCombes . Revised on July 23, 2023.

The conclusion is the final paragraph of your essay . A strong conclusion aims to:

Tie together the essay’s main points
Show why your argument matters
Leave the reader with a strong impression

Your conclusion should give a sense of closure and completion to your argument, but also show what new questions or possibilities it has opened up.

This conclusion is taken from our annotated essay example , which discusses the history of the Braille system. Hover over each part to see why it’s effective.

Braille paved the way for dramatic cultural changes in the way blind people were treated and the opportunities available to them. Louis Braille’s innovation was to reimagine existing reading systems from a blind perspective, and the success of this invention required sighted teachers to adapt to their students’ reality instead of the other way around. In this sense, Braille helped drive broader social changes in the status of blindness. New accessibility tools provide practical advantages to those who need them, but they can also change the perspectives and attitudes of those who do not.

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Step 1: return to your thesis, step 2: review your main points, step 3: show why it matters, what shouldn’t go in the conclusion, more examples of essay conclusions, other interesting articles, frequently asked questions about writing an essay conclusion.

To begin your conclusion, signal that the essay is coming to an end by returning to your overall argument.

Don’t just repeat your thesis statement —instead, try to rephrase your argument in a way that shows how it has been developed since the introduction.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

Academic style
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See an example

Next, remind the reader of the main points that you used to support your argument.

Avoid simply summarizing each paragraph or repeating each point in order; try to bring your points together in a way that makes the connections between them clear. The conclusion is your final chance to show how all the paragraphs of your essay add up to a coherent whole.

To wrap up your conclusion, zoom out to a broader view of the topic and consider the implications of your argument. For example:

Does it contribute a new understanding of your topic?
Does it raise new questions for future study?
Does it lead to practical suggestions or predictions?
Can it be applied to different contexts?
Can it be connected to a broader debate or theme?

Whatever your essay is about, the conclusion should aim to emphasize the significance of your argument, whether that’s within your academic subject or in the wider world.

Try to end with a strong, decisive sentence, leaving the reader with a lingering sense of interest in your topic.

The easiest way to improve your conclusion is to eliminate these common mistakes.

Don’t include new evidence

Any evidence or analysis that is essential to supporting your thesis statement should appear in the main body of the essay.

The conclusion might include minor pieces of new information—for example, a sentence or two discussing broader implications, or a quotation that nicely summarizes your central point. But it shouldn’t introduce any major new sources or ideas that need further explanation to understand.

Don’t use “concluding phrases”

Avoid using obvious stock phrases to tell the reader what you’re doing:

“In conclusion…”
“To sum up…”

These phrases aren’t forbidden, but they can make your writing sound weak. By returning to your main argument, it will quickly become clear that you are concluding the essay—you shouldn’t have to spell it out.

Don’t undermine your argument

Avoid using apologetic phrases that sound uncertain or confused:

“This is just one approach among many.”
“There are good arguments on both sides of this issue.”
“There is no clear answer to this problem.”

Even if your essay has explored different points of view, your own position should be clear. There may be many possible approaches to the topic, but you want to leave the reader convinced that yours is the best one!

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Argumentative
Literary analysis

This conclusion is taken from an argumentative essay about the internet’s impact on education. It acknowledges the opposing arguments while taking a clear, decisive position.

The internet has had a major positive impact on the world of education; occasional pitfalls aside, its value is evident in numerous applications. The future of teaching lies in the possibilities the internet opens up for communication, research, and interactivity. As the popularity of distance learning shows, students value the flexibility and accessibility offered by digital education, and educators should fully embrace these advantages. The internet’s dangers, real and imaginary, have been documented exhaustively by skeptics, but the internet is here to stay; it is time to focus seriously on its potential for good.

This conclusion is taken from a short expository essay that explains the invention of the printing press and its effects on European society. It focuses on giving a clear, concise overview of what was covered in the essay.

The invention of the printing press was important not only in terms of its immediate cultural and economic effects, but also in terms of its major impact on politics and religion across Europe. In the century following the invention of the printing press, the relatively stationary intellectual atmosphere of the Middle Ages gave way to the social upheavals of the Reformation and the Renaissance. A single technological innovation had contributed to the total reshaping of the continent.

This conclusion is taken from a literary analysis essay about Mary Shelley’s Frankenstein . It summarizes what the essay’s analysis achieved and emphasizes its originality.

By tracing the depiction of Frankenstein through the novel’s three volumes, I have demonstrated how the narrative structure shifts our perception of the character. While the Frankenstein of the first volume is depicted as having innocent intentions, the second and third volumes—first in the creature’s accusatory voice, and then in his own voice—increasingly undermine him, causing him to appear alternately ridiculous and vindictive. Far from the one-dimensional villain he is often taken to be, the character of Frankenstein is compelling because of the dynamic narrative frame in which he is placed. In this frame, Frankenstein’s narrative self-presentation responds to the images of him we see from others’ perspectives. This conclusion sheds new light on the novel, foregrounding Shelley’s unique layering of narrative perspectives and its importance for the depiction of character.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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Your essay’s conclusion should contain:

A rephrased version of your overall thesis
A brief review of the key points you made in the main body
An indication of why your argument matters

The conclusion may also reflect on the broader implications of your argument, showing how your ideas could applied to other contexts or debates.

For a stronger conclusion paragraph, avoid including:

Important evidence or analysis that wasn’t mentioned in the main body
Generic concluding phrases (e.g. “In conclusion…”)
Weak statements that undermine your argument (e.g. “There are good points on both sides of this issue.”)

Your conclusion should leave the reader with a strong, decisive impression of your work.

The conclusion paragraph of an essay is usually shorter than the introduction . As a rule, it shouldn’t take up more than 10–15% of the text.

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How to Write a Research Paper Conclusion Section

What is a conclusion in a research paper?

The conclusion in a research paper is the final paragraph or two in a research paper. In scientific papers, the conclusion usually follows the Discussion section , summarizing the importance of the findings and reminding the reader why the work presented in the paper is relevant.

However, it can be a bit confusing to distinguish the conclusion section/paragraph from a summary or a repetition of your findings, your own opinion, or the statement of the implications of your work. In fact, the conclusion should contain a bit of all of these other parts but go beyond it—but not too far beyond!

The structure and content of the conclusion section can also vary depending on whether you are writing a research manuscript or an essay. This article will explain how to write a good conclusion section, what exactly it should (and should not) contain, how it should be structured, and what you should avoid when writing it.

You presented your general field of study to the reader in the introduction section, by moving from general information (the background of your work, often combined with a literature review ) to the rationale of your study and then to the specific problem or topic you addressed, formulated in the form of the statement of the problem in research or the thesis statement in an essay.

In the conclusion section, in contrast, your task is to move from your specific findings or arguments back to a more general depiction of how your research contributes to the readers’ understanding of a certain concept or helps solve a practical problem, or fills an important gap in the literature. The content of your conclusion section depends on the type of research you are doing and what type of paper you are writing. But whatever the outcome of your work is, the conclusion is where you briefly summarize it and place it within a larger context. It could be called the “take-home message” of the entire paper.

What to summarize in the conclusion

Your conclusion section needs to contain a very brief summary of your work , a very brief summary of the main findings of your work, and a mention of anything else that seems relevant when you now look at your work from a bigger perspective, even if it was not initially listed as one of your main research questions. This could be a limitation, for example, a problem with the design of your experiment that either needs to be considered when drawing any conclusions or that led you to ask a different question and therefore draw different conclusions at the end of your study (compared to when you started out).

Once you have reminded the reader of what you did and what you found, you need to go beyond that and also provide either your own opinion on why your work is relevant (and for whom, and how) or theoretical or practical implications of the study , or make a specific call for action if there is one to be made.

How to Write an Essay Conclusion

Academic essays follow quite different structures than their counterparts in STEM and the natural sciences. Humanities papers often have conclusion sections that are much longer and contain more detail than scientific papers. There are three main types of academic essay conclusions.

Summarizing conclusion

The most typical conclusion at the end of an analytical/explanatory/argumentative essay is a summarizing conclusion . This is, as the name suggests, a clear summary of the main points of your topic and thesis. Since you might have gone through a number of different arguments or subtopics in the main part of your essay, you need to remind the reader again what those were, how they fit into each other, and how they helped you develop or corroborate your hypothesis.

For an essay that analyzes how recruiters can hire the best candidates in the shortest time or on “how starving yourself will increase your lifespan, according to science”, a summary of all the points you discussed might be all you need. Note that you should not exactly repeat what you said earlier, but rather highlight the essential details and present those to your reader in a different way.

Externalizing conclusion

If you think that just reminding the reader of your main points is not enough, you can opt for an externalizing conclusion instead, that presents new points that were not presented in the paper so far. These new points can be additional facts and information or they can be ideas that are relevant to the topic and have not been mentioned before.

Such a conclusion can stimulate your readers to think about your topic or the implications of your analysis in a whole new way. For example, at the end of a historical analysis of a specific event or development, you could direct your reader’s attention to some current events that were not the topic of your essay but that provide a different context for your findings.

Editorial conclusion

In an editorial conclusion , another common type of conclusion that you will find at the end of papers and essays, you do not add new information but instead present your own experiences or opinions on the topic to round everything up. What makes this type of conclusion interesting is that you can choose to agree or disagree with the information you presented in your paper so far. For example, if you have collected and analyzed information on how a specific diet helps people lose weight, you can nevertheless have your doubts on the sustainability of that diet or its practicability in real life—if such arguments were not included in your original thesis and have therefore not been covered in the main part of your paper, the conclusion section is the place where you can get your opinion across.

How to Conclude an Empirical Research Paper

An empirical research paper is usually more concise and succinct than an essay, because, if it is written well, it focuses on one specific question, describes the method that was used to answer that one question, describes and explains the results, and guides the reader in a logical way from the introduction to the discussion without going on tangents or digging into not absolutely relevant topics.

Summarize the findings

In a scientific paper, you should include a summary of the findings. Don’t go into great detail here (you will have presented your in-depth results and discussion already), but do clearly express the answers to the research questions you investigated.

Describe your main findings, even if they weren’t necessarily the ones anticipated, and explain the conclusion they led you to. Explain these findings in as few words as possible.

Instead of beginning with “ In conclusion, in this study, we investigated the effect of stress on the brain using fMRI …”, you should try to find a way to incorporate the repetition of the essential (and only the essential) details into the summary of the key points. “ The findings of this fMRI study on the effect of stress on the brain suggest that …” or “ While it has been known for a long time that stress has an effect on the brain, the findings of this fMRI study show that, surprisingly… ” would be better ways to start a conclusion.

You should also not bring up new ideas or present new facts in the conclusion of a research paper, but stick to the background information you have presented earlier, to the findings you have already discussed, and the limitations and implications you have already described. The one thing you can add here is a practical recommendation that you haven’t clearly stated before—but even that one needs to follow logically from everything you have already discussed in the discussion section.

Discuss the implications

After summing up your key arguments or findings, conclude the paper by stating the broader implications of the research , whether in methods , approach, or findings. Express practical or theoretical takeaways from your paper. This often looks like a “call to action” or a final “sales pitch” that puts an exclamation point on your paper.

If your research topic is more theoretical in nature, your closing statement should express the significance of your argument—for example, in proposing a new understanding of a topic or laying the groundwork for future research.

Future research example

Future research into education standards should focus on establishing a more detailed picture of how novel pedagogical approaches impact young people’s ability to absorb new and difficult concepts. Moreover, observational studies are needed to gain more insight into how specific teaching models affect the retention of relationships and facts—for instance, how inquiry-based learning and its emphasis on lateral thinking can be used as a jumping-off point for more holistic classroom approaches.

Research Conclusion Example and Outline

Let’s revisit the study on the effect of stress on the brain we mentioned before and see what the common structure for a conclusion paragraph looks like, in three steps. Following these simple steps will make it easy for you to wrap everything up in one short paragraph that contains all the essential information:

One: Short summary of what you did, but integrated into the summary of your findings:

While it has been known for a long time that stress has an effect on the brain, the findings of this fMRI study in 25 university students going through mid-term exams show that, surprisingly, one’s attitude to the experienced stress significantly modulates the brain’s response to it.

Note that you don’t need to repeat any methodological or technical details here—the reader has been presented with all of these before, they have read your results section and the discussion of your results, and even (hopefully!) a discussion of the limitations and strengths of your paper. The only thing you need to remind them of here is the essential outcome of your work.

Two: Add implications, and don’t forget to specify who this might be relevant for:

Students could be considered a specific subsample of the general population, but earlier research shows that the effect that exam stress has on their physical and mental health is comparable to the effects of other types of stress on individuals of other ages and occupations. Further research into practical ways of modulating not only one’s mental stress response but potentially also one’s brain activity (e.g., via neurofeedback training) are warranted.

This is a “research implication”, and it is nicely combined with a mention of a potential limitation of the study (the student sample) that turns out not to be a limitation after all (because earlier research suggests we can generalize to other populations). If there already is a lot of research on neurofeedback for stress control, by the way, then this should have been discussed in your discussion section earlier and you wouldn’t say such studies are “warranted” here but rather specify how your findings could inspire specific future experiments or how they should be implemented in existing applications.

Three: The most important thing is that your conclusion paragraph accurately reflects the content of your paper. Compare it to your research paper title , your research paper abstract , and to your journal submission cover letter , in case you already have one—if these do not all tell the same story, then you need to go back to your paper, start again from the introduction section, and find out where you lost the logical thread. As always, consistency is key.

Problems to Avoid When Writing a Conclusion

Do not suddenly introduce new information that has never been mentioned before (unless you are writing an essay and opting for an externalizing conclusion, see above). The conclusion section is not where you want to surprise your readers, but the take-home message of what you have already presented.
Do not simply copy your abstract, the conclusion section of your abstract, or the first sentence of your introduction, and put it at the end of the discussion section. Even if these parts of your paper cover the same points, they should not be identical.
Do not start the conclusion with “In conclusion”. If it has its own section heading, that is redundant, and if it is the last paragraph of the discussion section, it is inelegant and also not really necessary. The reader expects you to wrap your work up in the last paragraph, so you don’t have to announce that. Just look at the above example to see how to start a conclusion in a natural way.
Do not forget what your research objectives were and how you initially formulated the statement of the problem in your introduction section. If your story/approach/conclusions changed because of methodological issues or information you were not aware of when you started, then make sure you go back to the beginning and adapt your entire story (not just the ending).

Consider Receiving Academic Editing Services

When you have arrived at the conclusion of your paper, you might want to head over to Wordvice AI’s AI Writing Assistant to receive a free grammar check for any academic content.

After drafting, you can also receive English editing and proofreading services , including paper editing services for your journal manuscript. If you need advice on how to write the other parts of your research paper , or on how to make a research paper outline if you are struggling with putting everything you did together, then head over to the Wordvice academic resources pages , where we have a lot more articles and videos for you.

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How to write a conclusion for a research paper

Research paper conclusions provide closure for your paper—but they can be difficult to write. What should you include? In this post, we discuss how to write a conclusion for a research paper.

What is a conclusion?

The conclusion to a research paper sums of your main argument and provides closure for your reader. It will return to your thesis statement and revisit the ways that you proved it.

The content and format of your conclusion will ultimately differ depending on the subject of your paper. Some fields have more specific expectations for what needs to be included.

You should always check your assignment’s guidelines or rubric to ensure that you understand what your instructor expects in a research paper conclusion.

How to write a conclusion

In this section, we break down the main parts of a conclusion and provide tips on how to approach each one.

The opening of a conclusion

The point of a conclusion’s opening statement is to transition from the main body of your paper to the concluding section. Some types of research papers include section headers that label each part of the paper. In these cases, your reader will be able to clearly see that you’re about to conclude.

In most other cases, begin your conclusion with a signal that indicates that you’re moving into the concluding section of your paper. For instance, you might start your conclusion by stating “in conclusion,” “to conclude,” or “in sum.”

What you can include in a conclusion

Although you shouldn’t include any new data or evidence in a conclusion, you can include suggestions for further research, insights about how your research could be applied in different contexts, or a course of action.

The bulk of the conclusion should synthesize—not summarize—the main points of your paper. If your introduction included historical information or an anecdote, return to that information now.

Your conclusion should also answer the “so what” question: why is this research relevant? Who should care about your argument and why?

The ending of a conclusion

Finally, you’ll want to end your conclusion with a closing statement that wraps up your concluding section (and your paper as a whole).

Tips for writing a conclusion

1. don’t include new data or evidence.

Your conclusion should provide closure to your paper, so introducing new information is not appropriate and will likely confuse your reader.

2. Don’t simply restate your thesis

You should never simply copy and paste your thesis statement into your conclusion. Instead, revisit your thesis in light of the evidence and analysis that you put forth in the main body of your paper.

3. Provide closure for your reader

A strong conclusion provides closure for the reader by synthesizing the main points of the paper and putting to rest any questions that the reader may have during the process of reading. The best way to test if your conclusion provides closure is to ask someone to read your paper.

4. Make suggestions for further research

While conclusions should not introduce new data or arguments, they can include suggestions for further research. A single research paper never covers everything—there are always possible new angles and approaches.

Next steps for a successful research paper

Once you’ve written your conclusion, you should review what you’ve written and make revisions, as needed. Then, double-check that you’ve cited all borrowed material and that your paper has a bibliography with accurate citations.

Use BibGuru’s citation generator to quickly create accurate citations for the books, articles, websites, and other sources that you used in your research paper.

Frequently Asked Questions about how to write a conclusion for a research paper

A conclusion contains an opening statement (often a restatement of the thesis), recommendations for further studies or applications, and a closing statement.

Start by signaling to the reader that you are moving into the concluding section.

The length of your conclusion will depend on the length of your paper. Most research paper conclusions will be around 1-2 paragraphs.

End your conclusion with a closing statement that wraps up the paper and provides closure to your reader.

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Writing a Paper: Conclusions

Writing a conclusion.

A conclusion is an important part of the paper; it provides closure for the reader while reminding the reader of the contents and importance of the paper. It accomplishes this by stepping back from the specifics in order to view the bigger picture of the document. In other words, it is reminding the reader of the main argument. For most course papers, it is usually one paragraph that simply and succinctly restates the main ideas and arguments, pulling everything together to help clarify the thesis of the paper. A conclusion does not introduce new ideas; instead, it should clarify the intent and importance of the paper. It can also suggest possible future research on the topic.

An Easy Checklist for Writing a Conclusion

It is important to remind the reader of the thesis of the paper so he is reminded of the argument and solutions you proposed.

Think of the main points as puzzle pieces, and the conclusion is where they all fit together to create a bigger picture. The reader should walk away with the bigger picture in mind.

Make sure that the paper places its findings in the context of real social change.

Make sure the reader has a distinct sense that the paper has come to an end. It is important to not leave the reader hanging. (You don’t want her to have flip-the-page syndrome, where the reader turns the page, expecting the paper to continue. The paper should naturally come to an end.)

No new ideas should be introduced in the conclusion. It is simply a review of the material that is already present in the paper. The only new idea would be the suggesting of a direction for future research.

Conclusion Example

As addressed in my analysis of recent research, the advantages of a later starting time for high school students significantly outweigh the disadvantages. A later starting time would allow teens more time to sleep--something that is important for their physical and mental health--and ultimately improve their academic performance and behavior. The added transportation costs that result from this change can be absorbed through energy savings. The beneficial effects on the students’ academic performance and behavior validate this decision, but its effect on student motivation is still unknown. I would encourage an in-depth look at the reactions of students to such a change. This sort of study would help determine the actual effects of a later start time on the time management and sleep habits of students.

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Home » Research Report – Example, Writing Guide and Types

Research Report – Example, Writing Guide and Types

Table of Contents

Research Report

Definition:

Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner.

The purpose of a research report is to communicate the findings of the research to the intended audience, which could be other researchers, stakeholders, or the general public.

Components of Research Report

Components of Research Report are as follows:

Introduction

The introduction sets the stage for the research report and provides a brief overview of the research question or problem being investigated. It should include a clear statement of the purpose of the study and its significance or relevance to the field of research. It may also provide background information or a literature review to help contextualize the research.

Literature Review

The literature review provides a critical analysis and synthesis of the existing research and scholarship relevant to the research question or problem. It should identify the gaps, inconsistencies, and contradictions in the literature and show how the current study addresses these issues. The literature review also establishes the theoretical framework or conceptual model that guides the research.

Methodology

The methodology section describes the research design, methods, and procedures used to collect and analyze data. It should include information on the sample or participants, data collection instruments, data collection procedures, and data analysis techniques. The methodology should be clear and detailed enough to allow other researchers to replicate the study.

The results section presents the findings of the study in a clear and objective manner. It should provide a detailed description of the data and statistics used to answer the research question or test the hypothesis. Tables, graphs, and figures may be included to help visualize the data and illustrate the key findings.

The discussion section interprets the results of the study and explains their significance or relevance to the research question or problem. It should also compare the current findings with those of previous studies and identify the implications for future research or practice. The discussion should be based on the results presented in the previous section and should avoid speculation or unfounded conclusions.

The conclusion summarizes the key findings of the study and restates the main argument or thesis presented in the introduction. It should also provide a brief overview of the contributions of the study to the field of research and the implications for practice or policy.

The references section lists all the sources cited in the research report, following a specific citation style, such as APA or MLA.

The appendices section includes any additional material, such as data tables, figures, or instruments used in the study, that could not be included in the main text due to space limitations.

Types of Research Report

Types of Research Report are as follows:

Thesis is a type of research report. A thesis is a long-form research document that presents the findings and conclusions of an original research study conducted by a student as part of a graduate or postgraduate program. It is typically written by a student pursuing a higher degree, such as a Master’s or Doctoral degree, although it can also be written by researchers or scholars in other fields.

Research Paper

Research paper is a type of research report. A research paper is a document that presents the results of a research study or investigation. Research papers can be written in a variety of fields, including science, social science, humanities, and business. They typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections.

Technical Report

A technical report is a detailed report that provides information about a specific technical or scientific problem or project. Technical reports are often used in engineering, science, and other technical fields to document research and development work.

Progress Report

A progress report provides an update on the progress of a research project or program over a specific period of time. Progress reports are typically used to communicate the status of a project to stakeholders, funders, or project managers.

Feasibility Report

A feasibility report assesses the feasibility of a proposed project or plan, providing an analysis of the potential risks, benefits, and costs associated with the project. Feasibility reports are often used in business, engineering, and other fields to determine the viability of a project before it is undertaken.

Field Report

A field report documents observations and findings from fieldwork, which is research conducted in the natural environment or setting. Field reports are often used in anthropology, ecology, and other social and natural sciences.

Experimental Report

An experimental report documents the results of a scientific experiment, including the hypothesis, methods, results, and conclusions. Experimental reports are often used in biology, chemistry, and other sciences to communicate the results of laboratory experiments.

Case Study Report

A case study report provides an in-depth analysis of a specific case or situation, often used in psychology, social work, and other fields to document and understand complex cases or phenomena.

Literature Review Report

A literature review report synthesizes and summarizes existing research on a specific topic, providing an overview of the current state of knowledge on the subject. Literature review reports are often used in social sciences, education, and other fields to identify gaps in the literature and guide future research.

Research Report Example

Following is a Research Report Example sample for Students:

Title: The Impact of Social Media on Academic Performance among High School Students

This study aims to investigate the relationship between social media use and academic performance among high school students. The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The findings indicate that there is a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students. The results of this study have important implications for educators, parents, and policymakers, as they highlight the need for strategies that can help students balance their social media use and academic responsibilities.

Introduction:

Social media has become an integral part of the lives of high school students. With the widespread use of social media platforms such as Facebook, Twitter, Instagram, and Snapchat, students can connect with friends, share photos and videos, and engage in discussions on a range of topics. While social media offers many benefits, concerns have been raised about its impact on academic performance. Many studies have found a negative correlation between social media use and academic performance among high school students (Kirschner & Karpinski, 2010; Paul, Baker, & Cochran, 2012).

Given the growing importance of social media in the lives of high school students, it is important to investigate its impact on academic performance. This study aims to address this gap by examining the relationship between social media use and academic performance among high school students.

Methodology:

The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The questionnaire was developed based on previous studies and was designed to measure the frequency and duration of social media use, as well as academic performance.

The participants were selected using a convenience sampling technique, and the survey questionnaire was distributed in the classroom during regular school hours. The data collected were analyzed using descriptive statistics and correlation analysis.

The findings indicate that the majority of high school students use social media platforms on a daily basis, with Facebook being the most popular platform. The results also show a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students.

Discussion:

The results of this study have important implications for educators, parents, and policymakers. The negative correlation between social media use and academic performance suggests that strategies should be put in place to help students balance their social media use and academic responsibilities. For example, educators could incorporate social media into their teaching strategies to engage students and enhance learning. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. Policymakers could develop guidelines and policies to regulate social media use among high school students.

Conclusion:

In conclusion, this study provides evidence of the negative impact of social media on academic performance among high school students. The findings highlight the need for strategies that can help students balance their social media use and academic responsibilities. Further research is needed to explore the specific mechanisms by which social media use affects academic performance and to develop effective strategies for addressing this issue.

Limitations:

One limitation of this study is the use of convenience sampling, which limits the generalizability of the findings to other populations. Future studies should use random sampling techniques to increase the representativeness of the sample. Another limitation is the use of self-reported measures, which may be subject to social desirability bias. Future studies could use objective measures of social media use and academic performance, such as tracking software and school records.

Implications:

The findings of this study have important implications for educators, parents, and policymakers. Educators could incorporate social media into their teaching strategies to engage students and enhance learning. For example, teachers could use social media platforms to share relevant educational resources and facilitate online discussions. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. They could also engage in open communication with their children to understand their social media use and its impact on their academic performance. Policymakers could develop guidelines and policies to regulate social media use among high school students. For example, schools could implement social media policies that restrict access during class time and encourage responsible use.

References:

Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245.
Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Journal of the Research Center for Educational Technology, 8(1), 1-19.
Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657.
Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958.

Note*: Above mention, Example is just a sample for the students’ guide. Do not directly copy and paste as your College or University assignment. Kindly do some research and Write your own.

Applications of Research Report

Research reports have many applications, including:

Communicating research findings: The primary application of a research report is to communicate the results of a study to other researchers, stakeholders, or the general public. The report serves as a way to share new knowledge, insights, and discoveries with others in the field.
Informing policy and practice : Research reports can inform policy and practice by providing evidence-based recommendations for decision-makers. For example, a research report on the effectiveness of a new drug could inform regulatory agencies in their decision-making process.
Supporting further research: Research reports can provide a foundation for further research in a particular area. Other researchers may use the findings and methodology of a report to develop new research questions or to build on existing research.
Evaluating programs and interventions : Research reports can be used to evaluate the effectiveness of programs and interventions in achieving their intended outcomes. For example, a research report on a new educational program could provide evidence of its impact on student performance.
Demonstrating impact : Research reports can be used to demonstrate the impact of research funding or to evaluate the success of research projects. By presenting the findings and outcomes of a study, research reports can show the value of research to funders and stakeholders.
Enhancing professional development : Research reports can be used to enhance professional development by providing a source of information and learning for researchers and practitioners in a particular field. For example, a research report on a new teaching methodology could provide insights and ideas for educators to incorporate into their own practice.

How to write Research Report

Here are some steps you can follow to write a research report:

Identify the research question: The first step in writing a research report is to identify your research question. This will help you focus your research and organize your findings.
Conduct research : Once you have identified your research question, you will need to conduct research to gather relevant data and information. This can involve conducting experiments, reviewing literature, or analyzing data.
Organize your findings: Once you have gathered all of your data, you will need to organize your findings in a way that is clear and understandable. This can involve creating tables, graphs, or charts to illustrate your results.
Write the report: Once you have organized your findings, you can begin writing the report. Start with an introduction that provides background information and explains the purpose of your research. Next, provide a detailed description of your research methods and findings. Finally, summarize your results and draw conclusions based on your findings.
Proofread and edit: After you have written your report, be sure to proofread and edit it carefully. Check for grammar and spelling errors, and make sure that your report is well-organized and easy to read.
Include a reference list: Be sure to include a list of references that you used in your research. This will give credit to your sources and allow readers to further explore the topic if they choose.
Format your report: Finally, format your report according to the guidelines provided by your instructor or organization. This may include formatting requirements for headings, margins, fonts, and spacing.

Purpose of Research Report

The purpose of a research report is to communicate the results of a research study to a specific audience, such as peers in the same field, stakeholders, or the general public. The report provides a detailed description of the research methods, findings, and conclusions.

Some common purposes of a research report include:

Sharing knowledge: A research report allows researchers to share their findings and knowledge with others in their field. This helps to advance the field and improve the understanding of a particular topic.
Identifying trends: A research report can identify trends and patterns in data, which can help guide future research and inform decision-making.
Addressing problems: A research report can provide insights into problems or issues and suggest solutions or recommendations for addressing them.
Evaluating programs or interventions : A research report can evaluate the effectiveness of programs or interventions, which can inform decision-making about whether to continue, modify, or discontinue them.
Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies.

When to Write Research Report

A research report should be written after completing the research study. This includes collecting data, analyzing the results, and drawing conclusions based on the findings. Once the research is complete, the report should be written in a timely manner while the information is still fresh in the researcher’s mind.

In academic settings, research reports are often required as part of coursework or as part of a thesis or dissertation. In this case, the report should be written according to the guidelines provided by the instructor or institution.

In other settings, such as in industry or government, research reports may be required to inform decision-making or to comply with regulatory requirements. In these cases, the report should be written as soon as possible after the research is completed in order to inform decision-making in a timely manner.

Overall, the timing of when to write a research report depends on the purpose of the research, the expectations of the audience, and any regulatory requirements that need to be met. However, it is important to complete the report in a timely manner while the information is still fresh in the researcher’s mind.

Characteristics of Research Report

There are several characteristics of a research report that distinguish it from other types of writing. These characteristics include:

Objective: A research report should be written in an objective and unbiased manner. It should present the facts and findings of the research study without any personal opinions or biases.
Systematic: A research report should be written in a systematic manner. It should follow a clear and logical structure, and the information should be presented in a way that is easy to understand and follow.
Detailed: A research report should be detailed and comprehensive. It should provide a thorough description of the research methods, results, and conclusions.
Accurate : A research report should be accurate and based on sound research methods. The findings and conclusions should be supported by data and evidence.
Organized: A research report should be well-organized. It should include headings and subheadings to help the reader navigate the report and understand the main points.
Clear and concise: A research report should be written in clear and concise language. The information should be presented in a way that is easy to understand, and unnecessary jargon should be avoided.
Citations and references: A research report should include citations and references to support the findings and conclusions. This helps to give credit to other researchers and to provide readers with the opportunity to further explore the topic.

Advantages of Research Report

Research reports have several advantages, including:

Communicating research findings: Research reports allow researchers to communicate their findings to a wider audience, including other researchers, stakeholders, and the general public. This helps to disseminate knowledge and advance the understanding of a particular topic.
Providing evidence for decision-making : Research reports can provide evidence to inform decision-making, such as in the case of policy-making, program planning, or product development. The findings and conclusions can help guide decisions and improve outcomes.
Supporting further research: Research reports can provide a foundation for further research on a particular topic. Other researchers can build on the findings and conclusions of the report, which can lead to further discoveries and advancements in the field.
Demonstrating expertise: Research reports can demonstrate the expertise of the researchers and their ability to conduct rigorous and high-quality research. This can be important for securing funding, promotions, and other professional opportunities.
Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies. Producing a high-quality research report can help ensure compliance with these requirements.

Limitations of Research Report

Despite their advantages, research reports also have some limitations, including:

Time-consuming: Conducting research and writing a report can be a time-consuming process, particularly for large-scale studies. This can limit the frequency and speed of producing research reports.
Expensive: Conducting research and producing a report can be expensive, particularly for studies that require specialized equipment, personnel, or data. This can limit the scope and feasibility of some research studies.
Limited generalizability: Research studies often focus on a specific population or context, which can limit the generalizability of the findings to other populations or contexts.
Potential bias : Researchers may have biases or conflicts of interest that can influence the findings and conclusions of the research study. Additionally, participants may also have biases or may not be representative of the larger population, which can limit the validity and reliability of the findings.
Accessibility: Research reports may be written in technical or academic language, which can limit their accessibility to a wider audience. Additionally, some research may be behind paywalls or require specialized access, which can limit the ability of others to read and use the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Scope and Delimitations in Academic Research

Table of contents

1.1 Examples of Elements Included in the Scope
2.1 Examples of Delimitations in Research
3 Determining the Scope and Delimitation
4 Writing the Scope and Delimitations Section
5 Conclusion

Understanding the scope and delimitations of a study is crucial for defining its parameters and ensuring focused research efforts. What are delimitations in a research study? These components establish the boundaries within which the research will operate and clarify what the study aims to explore and achieve. This article delves into the significance of clearly defining the scope and every delimitation, how they guide the research focus, and their roles in shaping the research process. Additionally, it provides insights into determining these aspects and articulating them effectively in a research proposal or paper. Transitioning smoothly into the main discussion, let’s explore the importance of scope in research, guiding the focus.

The importance of Clearly Defining the Scope of the Study for Guiding Research Focus

The scope of research delineates its extent or range of inquiry, setting clear parameters for what the study will cover. It’s a foundational aspect that guides every step of the research process, from the formulation of research questions to the interpretation of results. Defining the scope helps in focusing the research efforts, ensuring that the study remains manageable and within realistic bounds.

Understanding the scope and limitation of the study allows researchers to allocate resources efficiently, ensuring that every aspect of the study receives adequate attention. It also helps in avoiding the common pitfall of overreaching, which can dilute the research’s impact and make findings less actionable. By setting a defined scope, researchers can more easily communicate their work’s relevance, limitations and delimitations in the research process to stakeholders, enhancing the credibility and applicability of their findings. Furthermore, a well-defined scope can facilitate a more targeted and effective literature review, laying a solid foundation for the research study.

When navigating the complexities of defining a study’s scope, researchers might seek external support to ensure their research is concise, well-structured, and impactful. A writing service , PapersOwl offers a spectrum tailored to meet academic research’s unique demands. Their expertise can be particularly beneficial in refining research proposals, ensuring the scope is clearly communicated and aligned with academic standards. Engaging with such a service allows researchers to benefit from professional insights, which can enhance the coherence and focus of their work. This collaboration can be instrumental in identifying the most relevant study areas and avoiding unnecessary diversions. With PapersOwl’s support, researchers can ensure their project’s scope is well-defined and compellingly presented, making a strong case for its significance and feasibility. This partnership can be a strategic step towards achieving a study’s specific objectives, ensuring it contributes valuable insights within its defined boundaries.

Examples of Elements Included in the Scope

Defining the scope of a research project is akin to drawing a map for a journey; it outlines the terrain to be explored and the boundaries within which the exploration will occur. This clarity is essential for guiding the research process, ensuring the investigation remains focused and relevant. The scope encompasses various elements, each contributing to the overall direction and integrity of the study. Let’s delve into some of these key elements:

Research Objectives : The specific aim the study is designed to achieve.
Geographical Coverage: The physical or virtual locations where the research is conducted.
Time Frame: The period during which the study takes place, which could range from a few days to several years.
Subject: The specific topics or issues the research intends to address.
Population Being Studied: The group of individuals, organizations, or phenomena being investigated.

These components of the scope serve as critical navigational tools in the research journey. They ensure that the study remains grounded in its objectives, relevant to its intended audience or population, and manageable within its temporal and geographical constraints. By carefully defining these elements at the outset, researchers can avoid common pitfalls such as scope creep, where the study’s focus broadens uncontrollably, potentially diluting its impact and significance. A well-defined scope is instrumental in crafting a focused, coherent, and impactful research project.

Role of Delimitations in Qualitative Research

Delimitations in research examples specify the boundaries set by the investigator on what the study will not cover, distinguishing them from limitations, which are potential weaknesses in the study not controlled by the researcher. Delimitations are choices made to narrow the scope of a study, focusing on specific aspects while excluding others. In the intricate tapestry of research design, delimitations play a pivotal role in sharpening the focus and enhancing the clarity of a study. By explicitly stating what the research will not explore, delimitations help prevent the dispersion of the research efforts across too broad an area, thereby increasing the depth and specificity of the investigation. This strategic narrowing allows researchers to concentrate their inquiries on areas most likely to yield impactful insights, making efficient use of available resources and time.

One might wonder how to establish these boundaries effectively without compromising the potential breadth of discovery. Here, the expertise provided by platforms like PapersOwl, particularly their research paper help service, becomes invaluable. Their seasoned professionals can offer guidance on crafting a research design that is both focused and flexible, assisting in identifying and justifying delimitations that enhance the study’s relevance and feasibility. Through such collaboration, researchers can balance the scope and delimitation of the study, ensuring that it remains grounded in its objectives while open to unforeseen insights.

Furthermore, acknowledging delimitations in a research paper demonstrates a researcher’s critical understanding of their study’s context and constraints, enhancing the credibility of their work. It shows a mindful engagement with the research process, recognizing that by setting deliberate boundaries, the study can delve more deeply and meaningfully into its chosen area of inquiry. Thus, when thoughtfully articulated with support from research paper writing help, like that offered by PapersOwl, delimitation in research becomes a testament to the rigor and integrity of its effort.

Examples of Delimitations in Research

Delimitations in research are akin to the guardrails on a highway; they keep the investigation on track and prevent it from veering into less relevant or overly broad territories. Below are some examples of how researchers can apply delimitations to fine-tune their investigations:

Restricting the Study to Certain Age Groups: Focusing on a specific demographic, such as teenagers or the elderly.
Geographic Locations: Limiting the research to a particular country, city, or region.
Specific Periods: Studying a phenomenon during a particular time frame, ignoring other periods.

Setting these research delimitations is not about narrowing the vision of the research, but rather about sharpening its focus. It allows for a more thorough and nuanced exploration of the chosen subjects, leading to more precise findings and general delimitation meaning in research. Delimitations highlight the researcher’s awareness of the study’s scope and commitment to conducting a focused, manageable investigation.

Determining the Scope and Delimitation

Identifying the scope and delimitations of your research involves understanding the research problem deeply and recognizing what is feasible within the constraints of time, resources, and data availability. Strategies for determining these include:

Reviewing existing literature to identify gaps and opportunities.
Consulting with experts or advisors to refine research questions.
Considering data availability and methodological constraints.

Balancing the scope and delimitations involves ensuring the research is neither too broad, unmanageable, nor too narrow, limiting its significance. Crafting a research project that strikes the right balance between breadth and depth is a nuanced task. It requires a researcher to be acutely aware of where their study begins and ends, what it encompasses, and what it intentionally leaves out. This equilibrium is not found in isolation but through a diligent exploration of the field and an understanding of how to best position one’s work within it. A key step in this process is identifying and sourcing relevant literature and data, which can significantly influence the scope of research.

Leveraging resources such as PapersOwl’s guide on how to find sources for research papers can prove invaluable in this phase. This platform provides insights into locating credible and relevant information, ensuring that researchers build their work upon a solid foundation of existing knowledge. By understanding how to navigate the vast, effective ocean of available data, researchers can make informed decisions about the direction and limits of their study. This meticulous preparation is crucial for defining the scope and delimitations and justifying them within the context of the research proposal or paper. It demonstrates a researcher’s commitment to rigor and depth, showing that their choices are informed by a comprehensive understanding of the subject and its existing body of literature.

Writing the Scope and Delimitations Section

Articulating the scope and delimitations in a research paper or proposal is crucial for setting clear expectations. It should clearly define delimitations and what the study will and will not cover, providing a rationale for these choices. Effective wording and structure involve:

Stating the research objectives and questions upfront.
Describing the research methodology , data collection methods and analysis.
Outlining the geographical coverage, time frame, and subject matter.
Clearly stating the delimitations and the reasons behind them.

The presentation of the scope and delimitations within a research document not only guides the readers through the intentions of the research but also establishes a framework for evaluating the findings. It’s a critical section where transparency and precision are paramount, allowing the audience to grasp the extent of the study and the rationale behind its boundaries. This transparency is essential for the credibility of the research, as it demonstrates a conscious and deliberate effort to focus the investigation and acknowledges the existence of boundaries that the study does not cross.

To ensure clarity and impact, this section should seamlessly integrate with the overall narrative of the research proposal or paper. Researchers are advised to avoid jargon and overly technical language, making the research scope and delimitations accessible to a broader audience. This includes a layperson who may not have deep expertise in the field but an interest in the study’s outcomes. Additionally, it is beneficial to highlight how the defined study scope and delimitations contribute to addressing the research problem, filling knowledge gaps, or exploring uncharted territories.

Moreover, this part of the document offers an opportunity to discuss how the chosen delimitations enhance the study’s focus and depth. By justifying the exclusions, researchers can address potential critiques head-on, reinforcing the methodological choices and underscoring the study’s contribution to the field. This careful articulation ensures that the research is perceived as a well-thought-out endeavor, grounded in a strategic approach to inquiry.

The scope and delimitations of a study are foundational elements that guide the research process, setting clear boundaries and focusing efforts. By defining these aspects clearly, researchers can provide a clear roadmap for their investigation, ensuring that their work is both manageable and relevant. By consciously deciding what to exclude from the study, researchers can intensify their focus on the chosen subject, ensuring that the research efforts are concentrated where they are most needed and can be most effective. These self-imposed boundaries are critical for maintaining the study’s coherence and depth. This clarity not only aids in conducting the research but also in effectively communicating its implications, limits, and outcomes.

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Open access
Published: 07 April 2023

Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics

Sandra C. Matz 1 ,
Christina S. Bukow 2 ,
Heinrich Peters 1 ,
Christine Deacons 3 ,
Alice Dinu 5 na1 &
Clemens Stachl 4

Scientific Reports volume 13 , Article number: 5705 ( 2023 ) Cite this article

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Human behaviour

An Author Correction to this article was published on 21 June 2023

This article has been updated

Student attrition poses a major challenge to academic institutions, funding bodies and students. With the rise of Big Data and predictive analytics, a growing body of work in higher education research has demonstrated the feasibility of predicting student dropout from readily available macro-level (e.g., socio-demographics or early performance metrics) and micro-level data (e.g., logins to learning management systems). Yet, the existing work has largely overlooked a critical meso-level element of student success known to drive retention: students’ experience at university and their social embeddedness within their cohort. In partnership with a mobile application that facilitates communication between students and universities, we collected both (1) institutional macro-level data and (2) behavioral micro and meso-level engagement data (e.g., the quantity and quality of interactions with university services and events as well as with other students) to predict dropout after the first semester. Analyzing the records of 50,095 students from four US universities and community colleges, we demonstrate that the combined macro and meso-level data can predict dropout with high levels of predictive performance (average AUC across linear and non-linear models = 78%; max AUC = 88%). Behavioral engagement variables representing students’ experience at university (e.g., network centrality, app engagement, event ratings) were found to add incremental predictive power beyond institutional variables (e.g., GPA or ethnicity). Finally, we highlight the generalizability of our results by showing that models trained on one university can predict retention at another university with reasonably high levels of predictive performance.

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Introduction

In the US, only about 60% of full-time students graduate from their program 1 , 2 with the majority of those who discontinue their studies dropping out during their first year 3 These high attrition rates pose major challenges to students, universities, and funding bodies alike 4 , 5 .

Dropping out of university without a degree negatively impacts students’ finances and mental health. Over 65% of US undergraduate students receive student loans to help pay for college, causing them to incur heavy debts over the course of their studies 6 . According to the U.S. Department of Education, students who take out a loan but never graduate are three times more likely to default on loan repayment than students who graduate 7 . This is hardly surprising, given that students who drop out of university without a degree, earn 66% less than university graduates with a bachelor's degree and are far more likely to be unemployed 2 . In addition to financial losses, the feeling of failure often adversely impacts students’ well-being and mental health 8 .

At the same time, student attrition negatively impacts universities and federal funding bodies. For universities, student attrition results in an average annual revenue reduction of approximately $16.5 billion per year through the loss of tuition fees 9 , 10 . Similarly, student attrition wastes valuable resources provided by states and federal governments. For example, the US Department of Education Integrated Postsecondary Education Data System (IPEDS) shows that between 2003 and 2008, state and federal governments together provided more than $9 billion in grants and subsidies to students who did not return to the institution where they were enrolled for a second year 11 .

Given the high costs of attrition, the ability to predict at-risk students – and to provide them with additional support – is critical 12 , 13 . As most dropouts occur during the first year 14 , such predictions are most valuable if they can identify at-risk students as early as possible 13 , 15 , 16 . The earlier one can identify students who might struggle, the better the chances that interventions aimed at protecting them from gradually falling behind – and eventually discontinuing their studies – will be effective 17 , 18 .

Indicators of student retention

Previous research has identified various predictors of student retention, including previous academic performance, demographic and socio-economic factors, and the social embeddedness of a student in their home institution 19 , 20 , 21 , 22 , 23 .

Prior academic performance (e.g., high school GPA, SAT and ACT scores or college GPA) has been identified as one of the most consistent predictors of student retention: Students who are more successful academically are less likely to drop out 17 , 21 , 24 , 25 , 26 , 27 , 28 , 29 . Similarly, research has highlighted the role of demographic and socio-economic variables, including age, gender, and ethnicity 12 , 19 , 25 , 27 , 30 as well as socio-economic status 31 in predicting a students’ likelihood of persisting. For example, women are more likely to continue their studies than men 12 , 30 , 32 , 33 while White and Asian students are more likely to persist than students from other ethnic groups 19 , 27 , 30 . Moreover, a student’s socio-economic status and immediate financial situation have been shown to impact retention. Students are more likely to discontinue their studies if they are first generation students 34 , 35 , 36 or experience high levels of financial distress, (e.g., due to student loans or working nearly full time to cover college expenses) 37 , 38 . In contrast, students who receive financial support that does not have to be repaid post-graduation are more likely to complete their degree 39 , 40 .

While most of the outlined predictors of student retention are relatively stable intrapersonal characteristics and oftentimes difficult or costly to change, research also points to a more malleable pillar of retention: the students’ experience at university. In particular, the extent to which they are successfully integrated and socialized into the institution 16 , 22 , 41 , 42 . As Bean (2005) notes, “few would deny that the social lives of students in college and their exchanges with others inside and outside the institution are important in retention decisions” (p. 227) 41 . The extent to which a student is socially integrated and embedded into their institution has been studied in a number of ways, relating retention to the development of friendships with fellow students 43 , the student’s position in the social networks 16 , 29 , the experience of social connectedness 44 and a sense of belonging 42 , 45 , 46 . Taken together, these studies suggest that interactions with peers as well as faculty and staff – for example through participation in campus activities, membership of organizations, and the pursuit of extracurricular activities – help students better integrate into university life 44 , 47 . In contrast, a lack of social integration resulting from commuting (i.e., not living on campus with other students) has shown to negatively impact a student’s chances of completing their degree 48 , 49 , 50 , 51 . In short, the stronger a student is embedded and feels integrated into the university community – particularly in their first year – the less likely the student will drop out 42 , 52 .

Predicting retention using machine learning

A large proportion of research on student attrition has focused on understanding and explaining drivers of student retention. However, alongside the rise of computational methods and predictive modeling in the social sciences 53 , 54 , 55 , educational researchers and practitioners have started exploring the feasibility and value of data-driven approaches in supporting institutional decision making and educational effectiveness (for excellent overviews of the growing field see 56 , 57 ). In line with this broader trend, a growing body of work has shown the potential of predicting student dropout with the help of machine learning. In contrast to traditional inferential approaches, machine learning approaches are predominantly concerned with predictive performance (i.e., the ability to accurately forecast behavior that has not yet occurred) 54 . In the context of student retention this means: How accurately can we predict whether a student is going to complete or discontinue their studies (in the future) by analyzing their demographic and socio-economic characteristics, their past and current academic performance, as well as their current embeddedness in the university system and culture?

Echoing the National Academy of Education’s statement (2017) that “in the educational context, big data typically take the form of administrative data and learning process data, with each offering their own promise for educational research” (p.4) 58 , the vast majority of existing studies have focused on the prediction of student retention from demographic and socio-economic characteristics as well as students’ academic history and current performance 13 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 . In a recent study, Aulck and colleagues trained a model on the administrative data of over 66,000 first-year students enrolled in a public US university (e.g., race, gender, highschool GPA, entrance exam scores and early college performance/transcript data) to predict whether they would re-enroll in the second year and eventually graduate 59 . Specifically, they used a range of linear and non-linear machine learning models (e.g., regularized logistic regression, k-nearest neighbor, random forest, support vector machine, and gradient boosted trees) to predict retention out-of-sample using a standard cross-validation procedures. Their model was able to predict dropouts with an accuracy of 88% and graduation with an accuracy of 81% (where 50% is chance).

While the existing body of work provides robust evidence for the potential of predictive models for identifying at-risk students, it is based on similar sets of macro-level data (e.g., institutional data, academic performance) or micro-level data (e.g., click-stream data). Almost entirely absent from this research is data on students’ daily experience and engagement with both other students and the university itself (meso-level). Although there have been a small number of studies trying to capture part of this experience by inferring social networks from smart card transactions that were made by students in the same time and place 16 or engagement metrics with an open online course 67 , none of the existing work has offered a more holistic and comprehensive view on students’ daily experience. One potential explanation for this gap is that information about students’ social interactions with classmates or their day-to-day engagement with university services and events is difficult to track. While universities often have access to demographic or socio-economic variables through their Student Information Systems (SISs), and can easily track their academic performance, most universities do not have an easy way of capturing student’s deeper engagement with the system.

Research overview

In this research, we partner with an educational software company – READY Education – that offers a virtual one-stop interaction platform in the form of a smartphone application to facilitate communication between students, faculty, and staff. Students receive relevant information and announcements, can manage their university activities, and interact with fellow students in various ways. For example, the app offers a social media experience like Facebook, including private messaging, groups, public walls, and friendships. In addition, it captures students’ engagement with the university asking them to check into events (e.g., orientation, campus events, and student services) using QR code functionality and prompting them to rate their experience afterwards (see Methods for more details on the features we extracted from this data). As a result, the READY Education app allows us to observe a comprehensive set of information about students that include both (i) institutional data (i.e., demographic, and socio-economic characteristics as well as academic performance), and (ii) their idiosyncratic experience at university captured by their daily interactions with other students and the university services/events. Combining the two data sources captures a student’s profile more holistically and makes it possible to consider potential interactions between the variable sets. For example, being tightly embedded in a social support network of friends might be more important for retention among first-generation students who might not receive the same level of academic support or learn about implicit academic norms and rules from their parents.

Building on this unique dataset, we use machine learning models to predict student retention (i.e., dropout) from both institutional and behavioral engagement data. Given the desire to identify at-risk students as early as possible, we only use information gathered in the students’ first semester to predict whether the student dropped out at any point in time during their program. To thoroughly validate and scrutinize our analytical approach, generate insights for potential interventions, and probe the generalizability of our predictive models across different universities, we investigate the following three research questions:

How accurately can we predict a student's likelihood of discontinuing their studies using information from the first term of their studies (i.e., institutional data, behavioral engagement data, and a combination of both)?

Which features are the most predictive of student retention?

How well do the predictive models generalize across universities (i.e., how well can we predict student retention of students from one university if we use the model trained on data from another university and vice versa)?

Participants

We analyze de-identified data from four institutions with a total of 50,095 students (min = 476, max = 45,062). All students provided informed consent to the use of the anonymized data by READY Education and research partners. All experimental protocols were approved by the Columbia University Ethics Board, and all methods carried out were in accordance with the Board’s guidelines and regulations. The data stem from two sources: (a) Institutional data and (b) behavioral engagement data. The institutional data collected by the universities contain socio-demographics (e.g., gender, ethnicity), general study information (e.g., term of admission, study program), financial information (e.g., pell eligibility), students’ academic achievement scores (e.g., GPA, ACT) as well as the retention status. The latter indicated whether students continued or dropped out and serves as the outcome variable. As different universities collect different information about their students, the scope of institutional data varied between universities. Table 1 provides a descriptive overview of the most important sociodemographic characteristics for each of the four universities. In addition, it provides a descriptive overview of the app usage, including the average number of logs per student, the total number of sessions and logs, as well as the percentage of students in a cohort using the app (i.e., coverage). The broad coverage of students using the app, ranging between 70 and 98%, results in a largely representative sample of the student populations at the respective universities.

Notably, Universities 1–3 are traditional university campuses, while University 4 is a combination of 16 different community colleges. Given that there is considerable heterogeneity across campuses, the predictive accuracies for University 4 are a-priori expected to be lower than those observed for universities 1–3 (and partly speak to the generalizability of findings already). The decision to include University 4 as a single entity was based on the fact that separating out the 16 colleges would have resulted in an over-representation of community colleges that all share similar characteristics thereby artificially inflating the observed cross-university accuracies. Given these limitations (and the fact that the University itself collapsed the college campuses for many of their internal reports), we decided to analyze it as a single unit, acknowledging that this approach brings its own limitations.

The behavioral engagement data were generated through the app (see Table 1 for the specific data collection windows at each University). Behavioral engagement data were available in the form of time-stamped event-logs (i.e., each row in the raw data represented a registered event such as a tab clicked, a comment posted, a message sent). Each log could be assigned to a particular student via an anonymized, unique identifier. Across all four universities, the engagement data contained 7,477,630 sessions (Mean = 1,869,408, SD = 3,329,852) and 17,032,633 logs (Mean = 4,258,158, SD = 6,963,613) across all universities. For complete overview of all behavioral engagement metrics including a description see Table S1 in the Supplementary Materials.

Pre-processing and feature extraction

As a first step, we cleaned both the institutional and app data. For the institutional data, we excluded students who did not use the app and therefore could not be assigned a unique identifier. In addition, we excluded students without a term of admission to guarantee that we are only observing the students’ first semester. Lastly, we removed duplicate entries resulting from dual enrollment in different programs. For the app usage data, we visually inspected the variables in our data set for outliers that might stem from technical issues. We pre-processed data that reflected clicking through the app, named “clicked_[…]” and “viewed_[…]” (see Table S1 in the Supplementary Materials). A small number of observations showed unrealistically high numbers of clicks on the same tab in a very short period, which is likely a reflection of a student repeatedly clicking on a tab due to long loading time or other technical issues. To avoid oversampling these behaviors, we removed all clicks of the same type which were made by the same person less than one minute apart.

We extracted up to 462 features for each university across two broad categories: (i) institutional features and (ii) engagement features, using evidence from previous research as a reference point (see Table S2 in the Supplementary Materials for a comprehensive overview of all features and their availability for each of the universities). Institutional features contain students’ demographic, socio-economic and academic information. The engagement features represent the students’ behavior during their first term of studies. They can be further divided into app engagement and community engagement. The app engagement features represent the students’ behavior related to app usage, such as whether the students used the app before the start of the semester, how often they clicked on notifications or the community tabs, or whether their app use increased over the course of the semester. The community involvement features reflect social behavior and interaction with others, e.g., the number of messages sent, posts and comments made, events visited or a student’s position in the network as inferred from friendships and direct messages. Importantly, many of the features in our dataset will be inter-correlated. For example, living in college accommodation could signal higher levels of socio-economic status, but also make it more likely that students attend campus events and connect with other students living on campus. While intercorrelations among predictors is a challenge with standard inferential statistical techniques such as regression analyses, the methods we apply in this paper can account for a large number of correlated predictors.

Institutional features were directly derived from the data recorded by the institutions. As noted above, not all features were available for all universities, resulting in slightly different feature sets across universities. The engagement features were extracted from the app usage data. As we focused on an early prediction of drop-out, we restricted the data to event-logs that were recorded in the respective students' first term. Notably, the data captures students’ engagement as a time-stamped series of events, offering fine-grained insights into their daily experience. For reasons of simplicity and interpretability (see research question 2), we collapse the data into a single entry for each student. Specifically, we describe a student’s overall experience during the first semester, by calculating distribution measures for each student such as the arithmetic mean, standard deviation, kurtosis, skewness, and sum values. For example, we calculate how many daily messages a particular student sent or received during their first semester, or how many campus events they attended in total. However, we also account for changes in a student’s behavior over time by calculating more complex features such as entropy (e.g., the extent to which a person has frequent contact with few people or the same degree of contact with many people) and the development of specific behaviors over time measured by the slope of regression analyses, as well as features representing the regularity of behavior (e.g., the deviation of time between sending messages). Overall, the feature set was aimed at describing a student’s overall engagement with campus resources and other students during the first semester as well as changed in engagement over time. Finally, we extracted some of the features separately for weekdays and weekends to account for differences and similarities in students’ activities during the week and the weekend. For example, little social interaction on weekdays might predict retention differently than little social interaction on the weekend.

We further cleaned the data by discarding participants for whom the retention status was missing and those in which 95% or more of the values were zero or missing. Furthermore, features were removed if they showed little or no variance across participants, which makes them essentially meaningless in a prediction task. Specifically, we excluded numerical features which showed the same values for more than 90% of observations and categorical features which showed the same value for all observations.

In addition to these general pre-processing procedures, we integrated additional pre-processing steps into the resampling prior to training the models to avoid an overestimation of model performance 68 . To prevent problems with categorical features that occur when there are fewer levels in the test than in the training data, we first removed categories that did not occur in the training data. Second, we removed constant categorical features containing a single value only (and therefore no variation). Third, we imputed missing values using the following procedures: Categorical features were imputed with the mode. Following commonly used approaches to dealing with missing data, the imputation of numeric features varied between the learners. For the elastic net, we imputed those features with the median. For the random forest, we used twice the maximum to give missing values a distinct meaning that would allow the model to leverage this information. Lastly, we used the "Synthetic Minority Oversampling Technique" (SMOTE) to create artificial examples for the minority class in the training data 69 . The only exception was University 4 which followed a different procedure due to the large sample size and estimated computing power for implementing SMOTE. Instead of oversampling minority cases, we downsampled majority cases such that the positive and negative class were balanced. This was done to address the class imbalance caused by most students continuing their studies rather than dropping out 12 .

Predictive modeling approach

We predicted the retention status (1 = dropped out, 0 = continued) in a binary prediction task, with three sets of features: (1) institutional features (2) engagement features, and (3) a combined set of all features. To ensure the robustness of our predictions and to identify the model which is best suited for the current prediction context 54 , we compared a linear classifier ( elastic net; implemented in glmnet 4.1–4) 70 , 71 and a nonlinear classifier ( random forest ; implemented in randomForest 4.7–1) 72 , 73 . Both models are particularly well suited for our prediction context and are common choices in computational social science. That is, simple linear or logistic regression models are not suitable to work with datasets that have many inter-correlated predictors (in our case, a total of 462 predictors many of which are highly correlated) due to a high risk of overfitting. Both the elastic net and the random forest algorithm can effectively utilize large feature sets while reducing the risk of overfitting. We evaluate the performance of our six models for each school (2 algorithms and 3 feature sets), using out-of-sample benchmark experiments that estimate predictive performance and compare it against a common non-informative baseline model. The baseline represents a null-model that does not include any features, but instead always predicts the majority class, which in our samples means “continued.” 74 Below, we provide more details about the specific algorithms (i.e., elastic net and random forest), the cross-validation procedure, and the performance metrics we used for model evaluation.

Elastic net model

The elastic net is a regularized regression approach that combines advantages of ridge regression 75 with those of the LASSO 76 and is motivated by the need to handle large feature sets. The elastic net shrinks the beta-coefficients of features that add little predictive value (e.g., intercorrelated, little variance). Additionally, the elastic net can effectively remove variables from the model by reducing the respective beta coefficients to zero 70 . Unlike classical regression models, the elastic net does not aim to optimize the sum of least squares, but includes two penalty terms (L1, L2) that incentivize the model to reduce the estimated beta value of features that do not add information to the model. Combining the L1 (the sum of absolute values of the coefficients) and L2 (the sum of the squared values of the coefficients) penalties, elastic net addresses the limitations of alternative linear models such as LASSO regression (not capable of handling multi-collinearity) and Ridge Regression (may not produce sparse-enough solutions) 70 .

Formally, following Hastie & Qian (2016) the model equation of elastic net for binary classification problems can be written as follows 77 . Suppose the response variable takes values in G = {0,1}, y i denoted as I(g i = 1), the model formula is written as

After applying the log-odds transformation, the model formula can be written as

The objective function for logistic regression is the penalized negative binomial log-likelihood

where λ is the regularization parameter that controls the overall strength of the regularization, α is the mixing parameter that controls the balance between L1 and L2 regularization with α values closer to zero to result in sparser models (lasso regression α = 1, ridge regression α = 0). β represents coefficients of the regression model, ||β|| 1 is the is the L1 norm of the coefficients (the sum of absolute values of the coefficients), ||β|| 2 is the L2 norm of the coefficients (the sum of the squared values of the coefficients).

The regularized regression approach is especially relevant for our model because many of the app-based engagement features are highly correlated (e.g., the number of clicks is related to the number of activities registered in the app). In addition, we favored the elastic net algorithm over more complex alternatives, because the regularized beta coefficients can be interpreted as feature importance, allowing insights into which predictors are most informative of college dropout 78 , 79 .

Random forest model

Random forest models are a widely used ensemble learning method that grows many bagged and decorrelated decision trees to come up with a “collective” prediction of the outcome (i.e., the outcome that is chosen by most trees in a classification problem) 72 . Individual decision trees recursively split the feature space (rules to distinguish classes) with the goal to separate the different classes of the criterion (drop out vs. remain in our case). For a detailed description of how individual decision trees operate and translate to a random forest see Pargent, Schoedel & Stachl 80 .

Unlike the elastic net, random forest models can account for nonlinear associations between features and criterion and automatically include multi-dimensional interactions between features. Each decision tree in a random forest considers a random subset of bootstrapped cases and features, thereby increasing the variance of predictions across trees and the robustness of the overall prediction. For the splitting in each node of each tree, a random subset of features (mtry hyperparameter that we optimize in our models) are used by randomly drawing from the total set. For each split, all combinations of split variables and split points are compared, with the model choosing the splits that optimize the separation between classes 72 .

The random forest algorithm can be formally described as follows (verbatim from Hastie et al., 2016, p. 588):

For b = 1 to B:

Draw a bootstrap sample of size N from the training data.

Grow a decision tree to the bootstrapped data, by recursively repeating the following steps for each terminal node of the tree, until the minimum node size is reached.

Select m variables at random from the p variables.

Pick the best variable/split-point among the m according to the loss function (in our case Gini-impurity decrease)

Split the node into two daughter nodes.

Output the ensemble of trees

New predictions can then be made by generating a prediction for each tree and aggregating the results using majority vote.

The aggregation of predictions across trees in random forests improves the prediction performance compared to individual decision trees, as it can benefit from the trees’ variance and greatly reduces it to arrive at a single prediction 72 , 81 .

(Nested) Cross-validation: Out-of-sample model evaluation

We evaluate the performance of our predictive models using an out-of-sample validation approach. The idea behind out-of-sample validation is to increase the likelihood that a model will accurately predict student dropout on new data (e.g. new students) by using different datasets when training and evaluating the model. A commonly used, efficient technique for out-of-sample validation is to repeatedly fit (cf. training) and evaluate (cf. testing) models on non-overlapping parts of the same datasets and to combine the individual estimates across multiple iterations. This procedure – known as cross-validation – can also be used for model optimization (e.g., hyperparameter-tuning, pre-processing, variable selection), by repeatedly evaluating different settings for optimal predictive performance. When both approaches are combined, evaluation and optimization steps need to be performed in a nested fashion to ensure a strict separation of training and test data for a realistic out-of-sample performance estimation. The general idea is to emulate all modeling steps in each fold of the resampling as if it were a single in-sample model. Here, we use nested cross-validation to estimate the predictive performance of our models, to optimize model hyperparameters, and to pre-process data. We illustrate the procedure in Fig. 1 .

Schematic cross-validation procedure for out-of-sample predictions. The figure shows a tenfold cross-validation in the outer loop which is used to estimate the overall performance of the model by comparing the predicted outcomes for each student in the previously unseen test set with their actual outcomes. Within each of the 10 outer loops, a fivefold cross-validation in the inner loop is used to finetune model hyperparameters by evaluating different model settings.

The cross-validation procedure works as follows: Say we have a dataset with 1,000 students. In a first step, the dataset is split into ten different subsamples, each containing data from 100 students. In the first round, nine of these subsamples are used for training (i.e., fitting the model to estimate parameters, green boxes). That means, the data from the first 900 students will be included in training the model to relate the different features to the retention outcome. Once training is completed, the model’s performance can be evaluated on the data of the remaining 100 students (i.e., test dataset, blue boxes). For each student, the actual outcome (retained or discontinued, grey and black figures) is compared to the predicted outcome (retained or discontinued, grey and black figures). This comparison allows for the calculation of various performance metrics (see “ Performance metrics ” section below for more details). In contrast to the application of traditional inferential statistics, the evaluation process in predictive models separates the data used to train a model from the data used to evaluate these associations. Hence any overfitting that occurs at the training stage (e.g., using researcher degrees of freedom or due to the model learning relationships that are unique to the training data), hurts the predictive performance in the testing stage. To further increase the robustness of findings and leverage the entire dataset, this process is repeated for all 10 subsamples, such that each subsample is used nine times for training and once for testing. Finally, the obtained estimates from those ten iterations are aggregated to arrive at a cross-validated estimate of model performance. This tenfold cross validation procedure is referred to as the “outer loop”.

In addition to the outer loop, our models also contain an “inner loop”. The inner loop consists of an additional cross-validation procedure that is used to identify ideal hyperparameter settings (see “ Hyperparameter tuning ” section below). That is, in each of the ten iterations of the outer loop, the training sample is further divided into a training and test set to identify the best parameter constellations before model evaluation in the outer loop. We used fivefold cross-validation in the inner loop. All analyses scripts for the pre-processing and modeling steps are available on OSF ( https://osf.io/bhaqp/?view_only=629696d6b2854aa9834d5745425cdbbc ).

Performance metrics

We evaluate model performance based on four different metrics. Our main metric for model performance is AUC (area under the received operating characteristics curve). AUC is commonly used to assess the performance of a model over a 50%-chance baseline, and can range anywhere between 0 and 1. The AUC metric captures the area under the receiver operating characteristic (ROC) curve, which plots the true positive rate (TPR or recall; i.e. the percentage of correctly classified dropouts among all students who actually dropped out), against the false positive rate (FPR; i.e. the percentage of students erroneously classified as dropouts among all the students who actually continued). When the AUC is 0.5, the model’s predictive performance is equal to chance or a coin flip. The closer to 1, the higher the model’s predictive performance in distinguishing between students who continued and those who dropped out.

In addition, we report the F1 score, which ranges between 0 and 1 82 . The F1 score is based on the model’s positive predictive value (or precision, i.e., the percentage of correctly classified dropouts among all students predicted to have dropped out) as well as the model's TPR. A high F1 score hence indicates that there are both few false positives and few false negatives.

Given the specific context, we also report the TPR and the true negative rates (TNR, i.e. the percentage of students predicted to continue among all students who actually continued). Depending on their objective, universities might place a stronger emphasis on optimizing the TPR to make sure no student who is at risk of dropping out gets overlooked or on optimizing the TNR to save resources and assure that students do not get overly burdened. Notably, in most cases, universities are likely to strive for a balance between the two, which is reflected in our main AUC measure. All reported performance metrics represent the mean predictive performance across the 10 cross-validation folds of the outer loop 54 .

Hyperparameter tuning

We used a randomized search with 50 iterations and fivefold cross-validation for hyperparameter tuning in the inner loop of our cross-validation. The randomized search algorithm fits models with hyperparameter configurations randomly selected from a previously defined hyperparameter space and then picks the model that shows the best generalized performance averaged over the five cross-validation folds. The best hyperparamter configuration is used for training in the outer resampling loop to evaluate model performance.

For the elastic net classifier, we tuned the regularization parameter lambda, the decision rule used to choose lambda, and the L1-ratio parameter. The search space for lambda encompassed the 100 glmnet default values 71 . The space of decision rules for lambda included lambda.min which chooses the value of lambda that results in the minimum mean cross-validation error, and lambda.1se which chooses the value of lambda that results in the most regularized model such that the cross-validation error remains within one standard error of the minimum. The search space for the L1-ratio parameter included the range of values between 0 (ridge) to 1 (lasso). For the random forest classifier, we tuned the number of features selected for each split within a decision tree (mtry) and the minimum node size (i.e., how many cases are required to be left in the resulting end-nodes of the tree). The search space for the number of input features per decision tree was set to a range of 1 to p, where p represents the dimensionality of the feature space. The search space for minimum node size was set to a range of 1 to 5. Additionally, for both models, we tuned the oversampling rate and the number or neighbors used to generate new samples utilized by the SMOTE algorithm. The oversampling rate was set to a range of 2 to 15 and the number of nearest neighbors was set to a range of 1 to 10.

RQ1: How accurately can we predict a student's likelihood of discontinuing their studies using information from the first term of their studies?

Figure 2 displays AUC scores (Y-axis) across the different universities (rows), separated by the different feature sets (colors) and predictive algorithms (X-axis labels). The figure displays the distribution of AUC accuracies across the 10 cross-validation folds, alongside their mean and standard deviation. Independent t-tests using Holm corrections for multiple comparisons indicate statistical differences in the predictive performance across the different models and feature sets within each university. Table 2 provides the predictive performance across all four metrics.

AUC performance across the four universities for different feature sets and model. Inst. = Institutional data. Engag. = Engagement data. (EN) = Elastic Net. (RF) = Random Forest.

Overall, our models showed high levels of predictive accuracies across universities, models, feature sets and performance metrics, significantly outperforming the baseline in all instances. The main performance metric AUC reached an average of 73% (where 50% is chance), with a maximum of 88% for the random forest model and the full feature set in University 1. Both institutional features and engagement features significantly contributed to predictive performance, highlighting the fact that a student’s likelihood to drop out is both a function of their more stable socio-demographic characteristics as well as their experience of campus life. In most cases, the joint model (i.e., the combination of institutional and engagement features) performed better than each of the individual models alone. Finally, the random forest models produced higher levels of predictive performance than the elastic net in most cases (average AUC elastic net = 70%, AUC random forest = 75%), suggesting that the features are likely to interact with one another in predicting student retention and might not always be linearly related to the outcome.

RQ2: Which features are the most predictive of student retention?

To provide insights into the underlying relationships between student retention and socio-demographic as well as behavioral features, we examined two indicators of feature importance that both offer unique insights. First, we calculated the zero-order correlations between the features and the outcome for each of the four universities. We chose zero-order correlations over elastic net coefficients as they represent the relationships unaltered by the model’s regularization procedure (i.e., the relationship between a feature and the outcome is shown independently of the importance of the other features in the model). To improve the robustness of our findings, we only included the variables that passed the threshold for data inclusion in our models and had less than 50% of the data imputed. The top third of Table 3 displays the 10 most important features (i.e., highest absolute correlation with retention). The sign in brackets indicates the direction of the effects with ( +) indicating a protective factor and (−) indicating a risk factor. Features that showed up in the top 10 for more than 1 university are highlighted in bold.

Second, we calculated permutation variable importance scores for the elastic net and random forest models. For the elastic net model, feature importance is reported as the model coefficient after shrinking the coefficients according to their incremental predictive power. Compared to the zero-order correlation, the elastic net coefficients hence identify the features that have the strongest unique variance. For the random forest models, feature importance is reported as a model-agnostic metric that estimates the importance of a feature by observing the drop in model predictive performance when the actual association between the feature and the outcome is broken by randomly shuffling observations 72 , 83 . A feature is considered important if shuffling its values increases the model error (and therefore decreases the model’s predictive performance). In contrast to the coefficients from the elastic net model, the permutation feature importance scores are undirected and do not provide insights into the specific nature of the relationship between the feature and the outcome. However, they account for the fact that some features might not be predictive themselves but could still prove valuable in the overall model performance because they moderate the impact of other features. For example, minority or first-generation students might benefit more from being embedded in a strong social network than majority students who do not face the same barriers and are likely to have a stronger external support network. The bottom of Table 3 displays the 10 most important features in the elastic net and random forest models (i.e., highest permutation variable importance).

Supporting the findings reported in RQ1, the zero-order correlations confirm that both institutional and behavioral engagement features play an important role in predicting student retention. Aligned with prior work, students’ performance (measured by GPA or ACT) repeatedly appeared as one of the most important predictors across universities and models. In addition, many of the engagement features (e.g., services attended, chat messages network centrality) are related to social activities or network features, supporting the notion that a student’s social connections and support play a critical role in student retention. In addition, the extent to which students are positively engaged with their institutions (e.g., by attending events and rating them highly) appears to play a critical role in preventing dropout.

RQ3: How well do the predictive models generalize across universities?

To test the generalizability of our models across universities, we used the predictive model trained on one university (e.g., University 1) to predict retention of the remaining three universities (e.g., Universities 2–4). Figures 3 A,B display the AUCs across all possible pairs, indicating which university was used for training (X-axis) and which was used for testing (Y-axis, see Figure S1 in the SI for graphs illustrating the findings for F1, TNR and TPR).

Performance (average AUC) of cross-university predictions.

Overall, we observed reasonably high levels of predictive performance when applying a model trained on one university to the data of another. The average AUC observed was 63% (for both the elastic net and the random forest), with the highest predictive performance reaching 74% (trained on University 1, predicting University 2), just 1%-point short of the predictive performance observed for the prediction from the universities own model (trained on University 2, predicting University 2). Contrary to the findings in RQ1, the random forest models did not perform better than the elastic net when making predictions for other universities. This suggests that the benefits afforded by the random forest models capture complex interaction patterns that are somewhat unique to each university but might not generalize well to new contexts. The main outlier in generalizability was University 4, where none of the other models reached accuracies much better than chance, and whose model produced relatively low levels of accuracies when predicting student retention across universities 1–2. This is likely a result of the fact that University 4 was qualitatively different from the other universities in several ways, including the fact that University 4 was a community college and consisted of 16 different campuses that were merged for the purpose of this analysis (see Methods for more details).

We show that student retention can be predicted from institutional data, behavioral engagement data, and their combination. Using data from over 50,000 students across four Universities, our predictive models achieve out-of-sample accuracies of up to 88% (where 50% is chance). Notably, while both institutional data and behavioral engagement data significantly predict retention, the combination of the two performs best in most instances. This finding is further supported by our feature importance analyses which suggest that both institutional and behavioral engagement features are among the most important predictors of student retention. Specifically, academic performance as measured by GPA and behavioral metrics associated with campus engagement (e.g., event attendances or ratings) or a student’s position in the network (e.g., closeness or centrality) were shown to consistently act as protective factors. Finally, we highlight the generalizability of our models across universities. Models trained on one university were able to predict student retention at another with reasonably high levels of predictive performance. As one might expect, the generalizability across universities heavily depends on the extent to which the universities are similar on important structural dimensions, with prediction accuracies dropping radically in cases where similarity is low (see low cross-generalization for University 4).

Contributions to the scientific literature

Our findings contribute to the existing literature in several ways. First, they respond to recent calls for more predictive research in psychology 54 , 55 as well as the use of Big Data analytics in education research 56 , 57 . Not only do our models consider socio-demographic characteristics that are collected by universities, but they also capture students’ daily experience and university engagement by tracking behaviors via the READY Education app. Our findings suggest, these more psychological predictors of student retention can improve the performance of predictive models above and beyond socio-demographic variables. This is consistent with previous findings suggesting that the inclusion of engagement metrics improves the performance of predictive models 16 , 84 , 85 . Overall, our models showed superior accuracies to models of former studies that were trained only on demographics and transcript records 15 , 25 or less comprehensive behavioral features 16 and provided results comparable to those reported in studies that additionally included a wide range of socio-economic variables 12 . Given that the READY Education app captures only a fraction of the students' actual experience, the high predictive accuracies make an even stronger case for the importance of student engagement in college retention.

Second, our findings provide insights into the features that are most important in predicting whether a student is going to drop out or not. By doing so they complement our predictive approach with layers of understanding that are conducive to not only validating our models but also generating insights into potential protective and risk factors. Most importantly, our findings highlight the relevance of the behavioral engagement metrics for predicting student retention. Most features identified as being important in the prediction were related to app and community engagement. In line with previous research, features indicative of early and deep social integration, such as interactions with peers and faculty or the development of friendships and social networks, were found to be highly predictive 16 , 41 . For example, it is reasonable to assume that a short time between app registration and the first visit of a campus event (one of the features identified as important) has a positive impact on retention, because campus events offer ideal opportunities for students to socialize 86 . Early participation in a campus event implies early integration and networking with others, protecting students from perceived stress 87 and providing better social and emotional support 88 . In contrast, a student who never attends an event or does so very late in the semester may be less connected to the campus life and the student community which in turn increases the likelihood of dropping out. This interpretation is strengthened by the fact that a high proportion of positive event ratings was identified as an important predictor of a student continuing their studies. Students who enjoy an event are likely to feel more comfortable, be embedded in the university life, make more connections, and build stronger connections. This might result in a virtuous cycle in which students continue attending events and over time create a strong social connection to their peers. As in most previous work, a high GPA score was consistently related to a higher likelihood of continuing one’s studies 21 , 24 . Although their importance varied across universities, ethnicity was also found to play a major role for retention, with consistent inequalities replicating in our predictive models 12 , 19 , 47 . For example, Black students were on average more likely to drop-out, suggesting that universities should dedicate additional resources to protect this group. Importantly, all qualitative interpretations are post-hoc. While many of the findings are intuitive and align with previous research on the topic, future studies should validate our results and investigate the causality underlying the effects in experimental or longitudinal within-person designs 54 , 78 .

Finally, our findings are the first to explore the extent to which the relationships between certain socio-demographic and behavioral characteristics might be idiosyncratic and unique to a specific university. By being able to compare the models across four different universities, we were able to show that many of the insights gained from one university can be leveraged to predict student retention at another. However, our findings also point to important boundary conditions: The more dissimilar universities are in their organizational structures and student experience, the more idiosyncratic the patterns between certain socio-demographic and behavioral features with student retention will be and the harder it is to merely translate general insights to the specific university campus.

Practical contributions

Our findings also have important practical implications. In the US, student attrition results in an average annual revenue loss of approximately $16.5 billion per year 9 , 10 and over $9 billion wasted in federal and state grants and subsidies that are awarded to students who do not finish their degree 11 . Hence, it is critical to predict potential dropouts as early and as accurately as possible to be able to offer dedicated support and allocate resources where they are needed the most. Our models rely exclusively on data collected in the first semester at university and are therefore an ideal “early warning” system for universities who want to predict whether their students will likely continue their studies or drop out at some point. Depending on the university’s resources and goals, the predictive models can be optimized for different performance measures. Indeed, a university might decide to focus on the true positive rate to capture as many dropouts as possible. While this would mean erroneously classifying “healthy “ students as potential dropouts, universities might decide that the burden of providing “unnecessary “ support to these healthy students is worth the reduced risk of missing a dropout. Importantly, our models go beyond mere socio-demographic variables and allow for a more nuanced, personal model that considers not just “who someone is” but also what their experience on campus looks like. As such, our models make it possible to acknowledge individuality rather than using over-generalized assessments of entire socio-demographic segments.

Importantly, however, it is critical to subject these models to continuous quality assurance. While predictive models could allow universities to flag at-risk students early, they could also perpetuate biases that get calcified in the predictive models themselves. For example, students who are traditionally less likely to discontinue their studies might have to pass a much higher level of dysfunctional engagement behavior before their file gets flagged as “at-risk”. Similarly, a person from a traditionally underrepresented group might receive an unnecessarily high volume of additional check-ins even though they are generally flourishing in their day-to-day experience. Given that being labeled as “at-risk” can be associated with stigma that could reinforce stigmas around historically marginalized groups, it will be critical to monitor both the performance of the model over time as well as the perception of its helpfulness among administrators, faculty, and students.

Limitations and future research

Our study has several limitations and highlights avenues for future research. First, our sample consisted of four US universities. Thus, our results are not necessarily generalizable to countries with more collectivistic cultures and other education systems such as Asia, where the reasons for dropping out might be different 89 , 90 , or Europe where most students work part-time jobs and live off-campus. Future research should investigate the extent to which our models can generalize to other cultural contexts and identify the features of student retention that are universally valid across contexts.

Second, our predictive models relied on app usage data. Therefore, our predictive approach could only be applied to students who decided to use the app. This selection, in and by itself, is likely to introduce a sampling bias, as students who decide to use the app might be more likely to retain in the first place, restricting the variance in observations, and excluding students for whom app usage data was not available. However, as our findings suggest, the institutional data alone provide predictive performance independent of the app features, making this a viable alternative for students who do not use the app.

Third, our predictive models rely on cross-sectional predictions. That is, we observe a students’ behavior over the course of an entire semester and based on the patterns observed in other students we predict whether that student is likely to drop out or not. Future research could try to improve both the predictive performance of the model and its usefulness for applied contexts by modeling within-person trends dynamically. Given enough data, the model could observe a person’s baseline behavior and identify changes from that baseline as potentially problematic. In fact, more social contact with other students might be considered a protective factor in our cross-sectional model. However, there are substantial individual differences in how much social contact individuals seek out and enjoy 91 . Hence, sending 10 chat messages a week might be considered a lot for one person, but very little for another. Future research should hence investigate whether the behavioral engagement features allow for a more dynamic within-person model that makes it possible to take base rates into account and provide a dynamic, momentary assessment of a student’s likelihood to drop out.

Fourth, although the engagement data was captured as a longitudinal time series with time-stamped events, we collapsed the data into a single set of cross-sectional features for each student. Although some of these features captures variation in behaviors over time (e.g., entropy and linear trends), future research should try to implement more advanced machine learning models to account for this time series data directly. For example, long short-term memory models (LSTMs) 92 – a type of recurrent neural network – are capable of learning patterns in longitudinal, sequential data like ours.

Fifth, even though the current research provides initial insights into the workings of the models by highlighting the importance of certain features, the conclusions that can be drawn from these analyses are limited as the importance metrics are calculated for the overall population. Future research could aim to calculate the importance of certain features at the individual level to test whether their importance varies across certain socio-demographic features. Estimating the importance of a person’s position in the social network on an individual level, for example, would make it possible to see whether the importance is correlated with institutional data such as minority or first-generation status.

Finally, our results lay the foundation for developing interventions that foster retention through shaping students’ experience at university 93 . Interventions which have been shown to have a positive effect on retention, include orientation programs and academic advising 94 , student support services like mentoring and coaching as well as need-based grants 95 . However, to date, the first-year experience programs meant to strengthen social integration of first year students, do not seem to have yielded positive results 96 , 97 . Our findings could support the development of interventions aimed at improving and maintaining student integration on campus. On a high level, the insights into the most important features provide an empirical path for developing relevant interventions that target the most important levers of student retention. For example, the fact that the time between registration and the first event attendance has such a big impact on student retention means that universities should do everything they can to get students to attend events as early as possible. Similarly, they could develop interventions that lead to more cohesive networks among cohorts and make sure that all students connect to their community. On a deeper, more sophisticated level, new approaches to model explainability could allow universities to tailor their intervention to each student 98 , 99 . For example, explainable AI makes it possible to derive decision rules for each student, indicating which features were critical in predicting the students’ outcome. While student A might be predicted to drop out because they are disconnected from the network, student B might be predicted to drop out because they don’t access the right information on the app. Given this information, universities would be able to personalize their offerings to the specific needs of the student. While student A might be encouraged to spend more time socializing with other students, student B might be reminded to check out important course information. Hence, predictive models could not only be used to identify students at risk but also provide an automated path to offering personalized guidance and support.

For every study that is discontinued, an educational dream shatters. And every shattered dream has a negative long-term impact both on the student and the university the student attended. In this study we introduce an approach to accurately predicting student retention after the first term. Our results show that student retention can be predicted with relatively high levels of predictive performance when considering institutional data, behavioral engagement data, or a combination of the two. By combining socio-demographic characteristics with passively observed behavioral traces reflecting a student’s daily activities, our models offer a holistic picture of students' university experiences and its relation to retention. Overall, such predictive models have great potential both for the early identification of at-risk students and for enabling timely, evidence-based interventions.

Data availability

Raw data are not publicly available due to their proprietary nature and the risks associated with de-anonymization, but they are available from the corresponding author on reasonable request. The pre-processed data and all analyses codes are available on OSF ( https://osf.io/bhaqp/ ) to facilitate reproducibility of our work. Data were analyzed using R, version 4.0.0 (R Core Team, 2020; see subsections for specific packages and versions used). The study’s design relies on secondary data and the analyses were not preregistered.

Change history

21 june 2023.

A Correction to this paper has been published: https://doi.org/10.1038/s41598-023-36579-2

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Sandra C. Matz & Heinrich Peters

Ludwig Maximilian University of Munich, Munich, Germany

Christina S. Bukow

Ready Education, Montreal, Canada

Christine Deacons

University of St. Gallen, St. Gallen, Switzerland

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S.C.M., C.B, A.D., H.P., and C.S. designed the research. C.D. and A.D. provided the data. S.C.M, C.B. and H.P. analyzed the data. S.C.M and C.B. wrote the manuscript. All authors reviewed the manuscript. Earlier versions of thi research were part of the C.B.’s masters thesis which was supervised by S.C.M. and C.S.

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The original online version of this Article was revised: Alice Dinu was omitted from the author list in the original version of this Article. The Author Contributions section now reads: “S.C.M., C.B, A.D., H.P., and C.S. designed the research. C.D. and A.D. provided the data. S.C.M, C.B. and H.P. analyzed the data. S.C.M and C.B. wrote the manuscript. All authors reviewed the manuscript. Earlier versions of this research were part of the C.B.’s masters thesis which was supervised by S.C.M. and C.S.” Additionally, the Article contained an error in Data Availability section and the legend of Figure 2 was incomplete.

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Matz, S.C., Bukow, C.S., Peters, H. et al. Using machine learning to predict student retention from socio-demographic characteristics and app-based engagement metrics. Sci Rep 13 , 5705 (2023). https://doi.org/10.1038/s41598-023-32484-w

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Mental health care is hard to find, especially for people with Medicare or Medicaid

Rhitu Chatterjee

A woman stands in the middle of a dark maze. Lights guide the way for her. It illustrates the concept of standing in front of a challenge and finding the right solution to move on.

With rates of suicide and opioid deaths rising in the past decade and children's mental health declared a national emergency , the United States faces an unprecedented mental health crisis. But access to mental health care for a significant portion of Americans — including some of the most vulnerable populations — is extremely limited, according to a new government report released Wednesday.

The report, from the Department of Health and Human Services' Office of Inspector General, finds that Medicare and Medicaid have a dire shortage of mental health care providers.

The report looked at 20 counties with people on Medicaid, traditional Medicare and Medicare Advantage plans, which together serve more than 130 million enrollees — more than 40% of the U.S. population, says Meridith Seife , the deputy regional inspector general and the lead author of the report.

Medicaid serves people on low incomes, and Medicare is mainly for people 65 years or older and those who are younger with chronic disabilities.

The report found fewer than five active mental health care providers for every 1,000 enrollees. On average, Medicare Advantage has 4.7 providers per 1,000 enrollees, whereas traditional Medicare has 2.9 providers and Medicaid has 3.1 providers for the same number of enrollees. Some counties fare even worse, with not even a single provider for every 1,000 enrollees.

"When you have so few providers available to see this many enrollees, patients start running into significant problems finding care," says Seife.

The findings are especially troubling given the level of need for mental health care in this population, she says.

"On Medicare, you have 1 in 4 Medicare enrollees who are living with a mental illness," she says. "Yet less than half of those people are receiving treatment."

Among people on Medicaid, 1 in 3 have a mental illness, and 1 in 5 have a substance use disorder. "So the need is tremendous."

The results are "scary" but "not very surprising," says Deborah Steinberg , senior health policy attorney at the nonprofit Legal Action Center. "We know that people in Medicare and Medicaid are often underserved populations, and this is especially true for mental health and substance use disorder care."

Among those individuals able to find and connect with a provider, many see their provider several times a year, according to the report. And many have to drive a long way for their appointments.

"We have roughly 1 in 4 patients that had to travel more than an hour to their appointments, and 1 in 10 had to travel more than an hour and a half each way," notes Seife. Some patients traveled two hours each way for mental health care, she says.

Mental illnesses and substance use disorders are chronic conditions that people need ongoing care for, says Steinberg. "And when they have to travel an hour, more than an hour, for an appointment throughout the year, that becomes unreasonable. It becomes untenable."

"We know that behavioral health workforce shortages are widespread," says Heather Saunders , a senior research manager on the Medicaid team at KFF, the health policy research organization. "This is across all payers, all populations, with about half of the U.S. population living in a workforce shortage."

But as the report found, that's not the whole story for Medicare and Medicaid. Only about a third of mental health care providers in the counties studied see Medicare and Medicaid patients. That means a majority of the workforce doesn't participate in these programs.

This has been well documented in Medicaid, notes Saunders. "Only a fraction" of providers in provider directories see Medicaid patients, she says. "And when they do see Medicaid patients, they often only see a few."

Lower reimbursement rates and a high administrative burden prevent more providers from participating in Medicaid and Medicare, the report notes.

"In the Medicare program, they set a physician fee rate," explains Steinberg. "Then for certain providers, which includes clinical social workers, mental health counselors and marriage and family therapists, they get reimbursed at 75% of that rate."

Medicaid reimbursements for psychiatric services are even lower when compared with Medicare , says Ellen Weber , senior vice president for health initiatives at the Legal Action Center.

"They're baking in those discriminatory standards when they are setting those rates," says Steinberg.

The new report recommends that the Centers for Medicare & Medicaid Services (CMS) take steps to increase payments to providers and lower administrative requirements. In a statement, CMS said it has responded to those recommendations within the report.

According to research by Saunders and her colleagues at KFF, many states have already started to take action on these fronts to improve participation in Medicaid.

Several have upped their payments to mental health providers. "But the scale of those increases ranged widely across states," says Saunders, "with some states limiting the increase to one provider type or one type of service, but other states having rate increases that were more across the board."

Some states have also tried to simplify and streamline paperwork, she adds. "Making it less complex, making it easier to understand," says Saunders.

But it's too soon to know whether those efforts have made a significant impact on improving access to providers.

CMS has also taken steps to address provider shortages, says Steinberg.

"CMS has tried to increase some of the reimbursement rates without actually fixing that structural problem," says Steinberg. "Trying to add a little bit here and there, but it's not enough, especially when they're only adding a percent to the total rate. It's a really small increase."

The agency has also started covering treatments and providers it didn't use to cover before.

"In 2020, Medicare started covering opioid treatment programs, which is where a lot of folks can go to get medications for their substance use disorder," says Steinberg.

And starting this year, Medicare also covers "mental health counselors, which includes addiction counselors, as well as marriage and family therapists," she adds.

While noteworthy and important, a lot more needs to be done, says Steinberg. "For example, in the substance use disorder space, a lot of addiction counselors do not have a master's degree. And that's one of their requirements to be a counselor in the Medicare program right now."

Removing those stringent requirements and adding other kinds of providers, like peer support specialists, is key to improving access. And the cost of not accessing care is high, she adds.

"Over the past two decades, [in] the older adult population, the number of overdose deaths has increased fourfold — quadrupled," says Steinberg. "So this is affecting people. It is causing deaths. It is causing people to go to the hospital. It increases [health care] costs."

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How Quickly Do Prices Respond to Monetary Policy?

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FRBSF Economic Letter 2024-10 | April 8, 2024

With inflation still above the Federal Reserve’s 2% objective, there is renewed interest in understanding how quickly federal funds rate hikes typically affect inflation. Beyond monetary policy’s well-known lagged effect on the economy overall, new analysis highlights that not all prices respond with the same strength or speed. Results suggest that inflation for the most responsive categories of goods and services has come down substantially from recent highs, likely due in part to more restrictive monetary policy. As a result, the contributions of these categories to overall inflation have fallen.

Monetary policy affects inflation with a lag. This means that, although interest rates react quickly when the Federal Reserve raises the federal funds rate, the effects on inflation are slower and indirect. Higher interest rates increase borrowing costs, slowing investment and overall demand, which ultimately eases the pressure on prices. Understanding the timing and strength of this mechanism is key for policymakers.

Many researchers have estimated the speed and strength of the economy’s response to monetary policy, notably Romer and Romer (2004). The focus is typically a broader measure of inflation, such as headline or core, which reflects an average across many goods and services. However, not all prices of the component goods and services react to monetary policy in the same way. For example, food and energy prices, which are excluded from core but included in headline inflation, often move more in response to global market fluctuations, such as changes in international oil prices, rather than to changes in domestic monetary policy.

In this Economic Letter , we estimate how prices of different goods and services respond to changes in the federal funds rate and use those estimates to build a monetary policy-responsive inflation index. We find substantial variation in how prices react to monetary policy, which suggests that understanding the makeup of overall inflation can provide insights into the transmission of monetary policy to inflation. The extent to which categories that are more responsive to the federal funds rate contribute to inflation affects how much slowing in economic activity is needed to reduce overall inflation. Our analysis indicates that recent ups and downs of inflation have been focused in categories that are most sensitive to monetary policy. Inflation rates for the most sensitive categories—and their contributions to headline inflation—rose from the first half of 2020 through mid-2022, reaching a higher peak than headline inflation, and then began to decline. The inflation rate for this most responsive group of goods and services categories is now close to its pre-2020 rate. Our findings suggest that the Fed’s rate hikes that began in March 2022 are exerting downward pressure on prices and will continue to do so in the near term. Our estimated lags are consistent with the view that the full effects of past policy tightening are still working their way through the economy.

Measuring how prices react to monetary policy

To understand which goods and services are most responsive to monetary policy, we need to determine how their prices react to changes in the federal funds rate, the Federal Reserve’s main policy rate. Because the Federal Reserve adjusts the federal funds rate target in response to macroeconomic developments, including inflation, we use a transformation of the federal funds rate in our estimation. This transformed series, developed by Romer and Romer (2004) and updated by Wieland and Yang (2020), captures the differences between Federal Reserve staff forecasts and the chosen target rate, leaving only policy shocks, or movements in the federal funds rate that are not driven by actual or anticipated changes in economic conditions. We use this series as a so-called instrument for the federal funds rate, such that our results can account for how the federal funds rate itself, rather than its transformation, affects inflation.

We use an approach developed by Jordà (2005) that compares two forecasts—with and without rate shocks—to estimate how the federal funds rate affects price movements over time. Specifically, we estimate the relationship between the federal funds rate and the cumulative percent change in prices, controlling for recent trends in the federal funds rate, inflation, and economic activity. Repeating this estimation over multiple horizons produces a forecast comparison, or impulse response function, that gives us an estimate of the expected percent change in prices following a rate increase. For example, applying this method to the headline personal consumption expenditures (PCE) price index indicates that four years after a 1 percentage point increase in the federal funds rate, overall prices are typically about 2.5% below what they would have been without the rate increase.

Creating a policy-responsive inflation index

We estimate impulse response functions separately for the 136 goods and services categories that collectively make up headline PCE inflation. Figure 1 shows examples of the largest cumulative percent price declines over a four-year period in response to a 1 percentage point increase in the federal funds rate. The goods and services categories selected as examples account for large shares of total expenditures in headline PCE inflation. We also include one example of the few categories where prices do not decline, higher education, shown as a small positive value.

Figure 1 Reaction to a policy rate increase: Selected PCE categories

The takeaway from Figure 1 is that headline PCE inflation is made up of categories that differ in their responsiveness to increases in the federal funds rate. Some respond more strongly, such as those with larger typical cumulative price declines, while others respond less strongly, such as those with smaller typical price declines. Focusing on the most responsive categories can shed light on how monetary policy has influenced the path of inflation over the post-pandemic period. We use our results to divide the categories into two groups of goods and services. The most responsive group (blue bars) contains goods and services whose largest cumulative percent price decline over a four-year window is in the top 50% of all such declines. The least responsive group (red bars) contains goods and services in the bottom 50%.

Following the methods in Shapiro (2022), we use these two groups, along with the share of total expenditures for each good or service, to create two new aggregate PCE inflation measures. Figure 2 shows their 12-month percent changes over time. The blue shading marks the period from mid-2019 until early 2020 when the Federal Reserve lowered the federal funds rate. The vertical yellow line marks the start of the most recent tightening cycle in March 2022. Inflation in the most responsive categories (blue line) is more volatile than overall headline PCE inflation (green line) from the Bureau of Economic Analysis (BEA), and inflation in the least responsive categories is less volatile (red line).

Figure 2 Most and least responsive inflation rates

After the start of the 2020 recession, inflation rates for both categories rose but have since come down from their recent peaks. This pattern is particularly pronounced for the most responsive inflation group, for which inflation peaked at 10.5% in mid-2022 and has fallen to 0.9% as of January 2024; this is just under its average of 1% from 2012, when the Federal Reserve officially adopted a numerical inflation objective, to 2019. Inflation in the least responsive group peaked later, in early 2023, and has fallen only slightly to 3.8% as of January 2024; it remains well above its 2012–2019 average of 1.8%.

How does policy-responsive inflation react to rate increases?

The inflation rates of categories in the most and least responsive groups can move for reasons beyond changes in the federal funds rate, such as global or national macroeconomic developments. To assess the specific role of policy rate increases, we use the methodology described earlier to estimate how the most and least responsive inflation groups tend to react to rate hikes.

The results in Figure 3 suggest that an increase in the federal funds rate typically starts exerting downward pressure on the most responsive prices after about 18 months, when the line showing the impulse response function falls below zero. Month-to-month price changes start falling after a little over a year, depicted when the slope drops below zero and stays negative. This is quicker than the response of overall headline prices from the BEA (not shown), which becomes negative after a little over 24 months and shows month-to-month declines after about 18 months.

Figure 3 Reaction of most and least responsive prices to rate hikes

Because we grouped inflation categories based on the size of their response, there is not necessarily a tie-in to the speed of each categories’ change. However, our results suggest that looking at the most responsive goods and services may also be a useful way of assessing how quickly monetary policy affects inflation.

Applying the typical impact timing of the most responsive group of goods and services to the most recent tightening cycle, shown by the federal funds rate line in Figure 4, leads to several conclusions. First, rate cuts from 2019 to early 2020 could have contributed upward price pressures starting in mid- to late 2020 and thus could explain some of the rise in inflation over this period. Second, the tightening cycle that began in March 2022 likely started putting downward pressure on prices in mid-2023 and will continue to do so in the near term. This is consistent with the view that the full effects of monetary policy tightening have yet to be felt. Finally, though inflation for the most responsive categories has been falling since mid-2022, the early part of this decline was likely to have been driven more by changes in prevailing economic conditions than by policy tightening, given estimated policy lags. Some research has considered whether policy lags have shortened (see, for example, Doh and Foerster 2021); however, because inflation began falling mere months after the first rate hike, the drop in inflation may have been too soon to be caused by policy action.

Figure 4 Headline inflation contributions and the federal funds rate

Our findings in this Letter are useful for broadening our understanding of how monetary policy affects inflation. For example, if inflation and the contributions to overall headline inflation are high in a set of categories that are more responsive to monetary policy, as was the case in early 2022, then rate hikes during the most recent tightening cycle are likely to continue to reduce inflation due to policy lags. On the other hand, though inflation in the least responsive categories may come down because of other economic forces, less inflation is currently coming from categories that are most responsive to monetary policy, perhaps limiting policy impacts going forward.

Doh, Taeyoung, and Andrew T. Foerster. 2022. “ Have Lags in Monetary Policy Transmission Shortened? ” FRB Kansas City Economic Bulletin (December 21).

Jordà, Òscar. 2005. “Estimation and Inference of Impulse Responses by Local Projections.” American Economic Review 95(1), pp. 161–182.

Romer, Christina, and David Romer. 2004. “A New Measure of Monetary Shocks: Derivation and Implications.” American Economic Review 94(4), pp. 1,055–1,084.

Shapiro, Adam. 2022. “ A Simple Framework to Monitor Inflation .” FRB San Francisco Working Paper 2020-29.

Wieland, Johannes, and Mu‐Jeung Yang. 2020. “Financial Dampening.” Journal of Money, Credit and Banking 52(1), pp. 79–113.

Opinions expressed in FRBSF Economic Letter do not necessarily reflect the views of the management of the Federal Reserve Bank of San Francisco or of the Board of Governors of the Federal Reserve System. This publication is edited by Anita Todd and Karen Barnes. Permission to reprint portions of articles or whole articles must be obtained in writing. Please send editorial comments and requests for reprint permission to [email protected]

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