A research proposal example, with notes on every section

This page is for students who learn best from a finished model. For the method behind each section, read the pillar guide on how to write a research proposal.

What does a research proposal look like?

A research proposal is a short document that states a research question, shows why it matters, and explains how you will answer it. In practice it is a sequence of headed sections, each answering one question a reviewer has. Here is the sample format both examples follow:

Notes after each section explain why it works.

Example 1: a quantitative research proposal (education)

This is an invented example. The course, institution and pass rates are fictional. The cited papers are real.

Title

Weekly Low-Stakes Retrieval Quizzes and Final Exam Performance in an Introductory Statistics Course: A Quasi-Experimental Study

Note: The title names the intervention, the outcome, the setting and the design. A reader knows what kind of study this is before reading the body.

1. Introduction

Introductory statistics is a required course for most social science degrees at [University], and it is the course students fail most often in their first year. Over the last three academic years, 36% of students in the course did not pass at the first attempt (internal data, [Department], 2026). Students who fail repeat the course and delay their degree.

Practicing retrieval of material, rather than rereading it, is a cheap, well-tested way to improve long-term retention. Retrieval practice improves delayed recall in laboratory studies (Roediger & Karpicke, 2006) and is rated as one of the most useful learning techniques for students (Dunlosky et al., 2013). Whether a simple weekly quiz improves exam results in a large, required, quantitative course at this institution has not been tested.

This study will test whether adding a weekly 10-question, ungraded quiz to the course improves final exam scores.

Note: The problem is local and measurable (a 36% non-pass rate), with a consequence. The second paragraph introduces the solution with two citations, and the last sentence states exactly what the study will do. No history of the field: the reader gets to the point in three paragraphs.

2. Research question and hypotheses

Research question: Do students who complete weekly low-stakes retrieval quizzes score higher on the final exam of an introductory statistics course than students who complete the standard course?

• H0: There is no difference in mean final exam score between the quiz and comparison sections, after adjusting for pre-course mathematics score.
• H1: Students in the quiz sections will have a higher mean final exam score than students in the comparison sections, after adjusting for pre-course mathematics score.

Objectives:

1. Measure final exam scores in quiz and comparison sections.
2. Compare adjusted mean scores between the two conditions.
3. Describe quiz completion rates and their association with exam scores.

Note: One question, a matched pair of hypotheses that name the covariate, and three objectives that each map to an analysis in section 4. Objective 3 is descriptive because quiz completion is not randomized, so the proposal does not claim a causal test.

3. Literature review

Laboratory evidence. The testing effect is one of the most replicated findings in learning research. In a well-known experiment, students who took practice tests on a prose passage recalled more of it a week later than students who restudied it, even though restudying produced better recall after five minutes (Roediger & Karpicke, 2006).

Classroom evidence. Reviews of applied research suggest that the effect survives the move from laboratory to classroom. A meta-analysis of practice testing found benefits across settings, formats and age groups (Adesope et al., 2017), and a later meta-analysis restricted to classroom studies found that quizzing improved learning compared with no quizzing or other activities (Yang et al., 2021). A systematic review of applied studies in schools and classrooms reached a similar conclusion (Agarwal et al., 2021).

The gap. Most classroom studies test retrieval practice on conceptual or verbal material, in courses where the quizzes count toward the grade. Fewer test ungraded quizzes in a large, required, quantitative course, where students must apply procedures as well as recall facts. The present study addresses that gap in one institution, with a pre-course measure of mathematics ability as a covariate.

Note: Organized by theme, not paper by paper, and each paragraph makes a claim with its evidence. The last paragraph names the gap precisely, which is what justifies a new study when meta-analyses already exist.

4. Methods

Design. A quasi-experimental, non-equivalent groups design with a pre-course covariate. Students enroll in one of four sections of the course; random assignment of individuals is not possible. Two sections, chosen by coin toss, will add weekly quizzes; the other two will follow the standard course.

Participants. All students enrolled in the four autumn sections (expected enrollment 260). Inclusion: enrolled at week 2 and consenting to the use of their course data. Exclusion: students who withdraw before the final exam.

Sample size. To detect a difference of d = 0.40 between two groups with a two-tailed test (a conservative choice for a directional hypothesis), alpha = .05 and power = .80, about 100 students per condition are needed (200 in total), calculated with G*Power (Faul et al., 2007). Allowing for 15% attrition, the study needs at least 236 enrolled students; expected enrollment is 260.

Intervention. Each week, quiz-section students complete a 10-question online quiz on the previous week's material, with feedback after submission. Quizzes are ungraded and take about 15 minutes. Comparison sections receive the same lectures and practice problems without the quiz.

Measures. (a) Final exam score (0 to 100), written and marked by staff blind to condition; (b) pre-course mathematics diagnostic score (0 to 40), already given to all students in week 1; (c) number of quizzes completed (0 to 10).

Analysis. Objective 2 will use an analysis of covariance (ANCOVA) with condition as the factor and the diagnostic score as the covariate, after checking homogeneity of regression slopes. Objectives 1 and 3 will use descriptive statistics and a Pearson correlation between quizzes completed and exam score within quiz sections. Because students are clustered in sections, a sensitivity analysis will use a multilevel model with section as a random effect. Analyses will be run in R.

Limitations. With four sections, section and instructor effects cannot be fully separated from the quiz effect. Each instructor will teach one quiz and one comparison section to reduce this.

Note: The longest section, on purpose. The sample size has a number and a reason, and the arithmetic adds up (200 / 0.85 = 236). Each objective has a named analysis. The main weakness, clustering by section, is admitted and reduced twice: in the design and in a multilevel sensitivity model.

5. Ethical considerations

The study uses course data and an educational activity that carries minimal risk. Students will receive an information sheet in week 2 and may opt out of the use of their data without any effect on their grade. Quiz completion is voluntary and ungraded. The data will be pseudonymized by an administrator outside the research team before analysis and stored on the university's secure drive for five years. The study will be submitted to the [University] Research Ethics Committee before the autumn term.

Note: Five sentences cover risk, consent, voluntariness, data protection and the reviewing board. The opt-out "without any effect on their grade" answers the main issue in classroom research: the instructor's power over students. See how to write an IRB application.

6. Timeline

Note: Ethics approval comes first, with two months before the term starts. A pilot is built in. Writing gets two months, not two weeks.

References

Adesope, O. O., Trevisan, D. A., & Sundararajan, N. (2017). Rethinking the use of tests: A meta-analysis of practice testing. Review of Educational Research, 87(3), 659–701. https://doi.org/10.3102/0034654316689306

Agarwal, P. K., Nunes, L. D., & Blunt, J. R. (2021). Retrieval practice consistently benefits student learning: A systematic review of applied research in schools and classrooms. Educational Psychology Review, 33(4), 1409–1453. https://doi.org/10.1007/s10648-021-09595-9

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. https://doi.org/10.1177/1529100612453266

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146

Roediger, H. L., III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. https://doi.org/10.1111/j.1467-9280.2006.01693.x

Yang, C., Luo, L., Vadillo, M. A., Yu, R., & Shanks, D. R. (2021). Testing (quizzing) boosts classroom learning: A systematic and meta-analytic review. Psychological Bulletin, 147(4), 399–435. https://doi.org/10.1037/bul0000309

Note: Six sources, each doing a job: mechanism, classroom evidence, power calculation. The list is in APA 7 format; see research proposal APA format.

Example 2: a short qualitative research proposal (public health)

This is an invented example. Background claims are shown as placeholders "(Author, Year)": in a real proposal you would cite studies from your own search. The methods references are real.

Title: Rural Community Pharmacists' Experiences of Providing Blood Pressure Checks: A Qualitative Interview Study

Introduction (summary). High blood pressure often goes undiagnosed in rural areas, where people live far from a general practice (Author, Year). Community pharmacies are often the nearest health service, and some health systems now pay pharmacies to offer blood pressure checks (Author, Year). Little is known about how rural pharmacists fit this service into their working day.

Research question. How do community pharmacists in rural areas of [Region] experience delivering a funded blood pressure check service? There is no hypothesis: the study explores experience rather than testing a prediction.

Methods. Semi-structured interviews of 30 to 45 minutes, online or by phone, with 12 to 15 pharmacists from pharmacies in rural postcodes, recruited through the regional pharmacy network with purposive sampling for pharmacy size and years in practice. Sample size will be judged during the study using the concept of information power, which links the number of participants needed to the study's aim, sample specificity and quality of dialogue (Malterud et al., 2016). Interviews will be transcribed and analyzed with reflexive thematic analysis (Braun & Clarke, 2006, 2019). Reporting will follow the COREQ checklist (Tong et al., 2007).

Ethics. Participants are professionals discussing their work; the main risk is identification in a small community. Quotes will be stripped of place names and pharmacy details. Consent will be recorded before each interview.

Timeline. Ethics review (months 1 to 2), recruitment and interviews (months 3 to 5), analysis (months 5 to 7), write-up (months 8 to 9).

Methods references. Braun and Clarke (2006, 2019), Malterud et al. (2016) and Tong et al. (2007). The full APA entries are Sources 7 to 10 below.

Note: A qualitative proposal justifies its sample with information power instead of a power calculation, names a specific analysis method with its source, and addresses the risk that matters here: identification in a small community.

What makes these research proposal examples work?

Both examples share five habits you can copy into your own proposal:

1. The question is narrow enough to answer with one design, in one setting, in under a year.
2. The gap is stated in one sentence at the end of the literature review.
3. The sample size has a reason: a power calculation or a qualitative sufficiency argument.
4. Every objective maps to an analysis that is named, not described vaguely.
5. Limitations are admitted and reduced, not hidden.

Draft and check your proposal in AI for Research

For a first draft, the Research proposal tool in Proposal Studio writes a whole proposal (15 credits) or one section (3 credits) from your topic and level, with the background citing real papers. The free research proposal generator runs 3 times a day without signing in. Then check the draft:

• Citation check (0 credits) confirms each reference exists in Crossref or OpenAlex and flags retractions and wrong years or authors.
• Reviewer, set to "proposal", scores each criterion out of 10 and quotes the passages that need work. On the free plan, a preview of the first 3,000 words (the full scorecard and top 3 comments) costs 3 credits.
• Export to Word or PDF (0 credits) for your own research proposal sample PDF.

The free plan has 45 credits a month; see pricing. No tool can tell you whether your idea is new or feasible at your institution: ask your supervisor.

FAQ

What does a research proposal look like?

A typical research proposal is 1,500 to 3,000 words with headings for the title, introduction, research question and objectives, literature review, methods, ethics, timeline and references. It reads as an argument: here is a problem, here is what we know, here is the gap, and here is a feasible way to fill it. Funded proposals add a budget and follow the funder's headings.

What is a good research proposal example for students?

A good example for students is one at the same level and in a similar field as yours, with a narrow question, a stated sample size with reasons, named analysis methods and a realistic timeline. Use examples to learn structure and reasoning, not wording. Copying an example's text is plagiarism, and examiners compare proposals across a cohort.

Can I copy a research proposal sample?

No. You can copy the structure and the headings, which are standard, but not the wording, the argument or the specific design. Universities run similarity checks on proposals, and a copied design rarely fits your question anyway. Use the sample to see what each section must contain, then write each part about your own study.

Where can I find a research proposal sample PDF?

Your own department is the best source: ask for proposals from past students who passed, since they match your marking criteria. Many university graduate schools also publish annotated examples. For grants, some funders and universities share funded applications. Treat any sample from another institution as a guide to structure, because limits and headings differ.

Does every research proposal need a hypothesis?

No. Quantitative studies that test a prediction should state hypotheses, usually as a null and alternative pair. Exploratory, descriptive and most qualitative studies use research questions instead, because they do not predict an outcome. The second example in this post is qualitative and has no hypothesis; the first is quantitative and has one.

Next steps

• Learn the method behind each section in how to write a research proposal.
• Format your proposal with research proposal APA format.
• Write the ethics part properly with how to write an IRB application.
• Write a sharper hypothesis with how to write a hypothesis.
• Start from a blank, copyable research proposal template.

Sources

Full APA entries for sources 1 to 6 are in Example 1's reference list.

1. Roediger & Karpicke (2006), Psychological Science. https://doi.org/10.1111/j.1467-9280.2006.01693.x
2. Dunlosky et al. (2013), Psychological Science in the Public Interest. https://doi.org/10.1177/1529100612453266
3. Adesope et al. (2017), Review of Educational Research. https://doi.org/10.3102/0034654316689306
4. Yang et al. (2021), Psychological Bulletin. https://doi.org/10.1037/bul0000309
5. Agarwal et al. (2021), Educational Psychology Review. https://doi.org/10.1007/s10648-021-09595-9
6. Faul et al. (2007), Behavior Research Methods. https://doi.org/10.3758/BF03193146
7. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
8. Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
9. Malterud, K., Siersma, V. D., & Guassora, A. D. (2016). Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 26(13), 1753–1760. https://doi.org/10.1177/1049732315617444
10. Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19(6), 349–357. https://doi.org/10.1093/intqhc/mzm042