35 ChatGPT Prompts That Accelerate Every Stage of Your Research

I'm starting research on [topic] in [discipline]. Help me map the intellectual landscape: What I know so far: [brief summary of your current understanding] Provide: the 3-5 major theoretical frameworks or schools of thought in this area, key debates and unresolved questions, seminal works and foundational papers I must read, how the field has evolved over the last 10-20 years, interdisciplinary connections (what other fields contribute?), and current "hot" research directions. For each framework, name key scholars associated with it. Organize as a conceptual map I can use to structure my literature review.

Help me critically analyze this research paper: Title: [title] Authors: [authors] Journal: [journal, year] Abstract: [paste abstract] Methodology: [describe if known] Key findings: [list main results] Analyze: the research question — is it clear, specific, and significant? Methodology — is it appropriate for the question? Are there design flaws? Validity — internal validity (can we trust the causal claims?) and external validity (can we generalize?). Sample — size, selection, representativeness. Statistical analysis — appropriate tests? Effect sizes reported? Limitations — what do the authors acknowledge vs what they miss? Bias — funding sources, author conflicts, selection bias in data. Rate the paper's overall contribution: groundbreaking, solid, incremental, or flawed.

I need to synthesize these sources for my literature review on [theme]: Source 1: [author, year] — [main argument/finding] Source 2: [author, year] — [main argument/finding] Source 3: [author, year] — [main argument/finding] Source 4: [author, year] — [main argument/finding] [add more as needed] Synthesize (not summarize) these sources by: identifying points of agreement and disagreement, grouping them by theoretical approach or methodology, tracing how ideas developed chronologically, finding gaps that none of them address, and connecting them to my research question: "[your RQ]." Write two versions: a structured analysis (bullet points showing relationships) and a flowing paragraph suitable for a literature review section.

Based on my reading of [topic], here are the major findings and themes in existing research: [Summarize 5-10 key findings from your reading] Help me identify research gaps: what populations or contexts have been understudied? What methodological approaches are missing (too much qualitative? too much quantitative? no mixed methods?)? What variables or relationships haven't been examined? What assumptions go unchallenged? Where do findings contradict each other without resolution? What practical applications haven't been tested? For each gap, assess: is this gap significant enough to justify a study? How feasible would it be to address? Would filling this gap advance the field?

I have [number] sources for my research on [topic]. Help me evaluate and rank them: [List each source: author, year, title, publication] Evaluate each source on: credibility (peer-reviewed? reputable journal? author expertise?), relevance (how directly does it address my research question?), currency (is it still valid or has the field moved on?), methodology quality (rigorous design? adequate sample?), citation impact (how often cited? by whom?), and bias risk (funding, author position, ideological lean). Create a matrix rating each source 1-5 on these criteria with a total score. Recommend: which sources to feature prominently, which to cite briefly, and which to drop.

The concept of [concept name] appears in multiple disciplines. I'm researching it from a [your discipline] perspective. Trace how this concept is understood across: [List 3-5 relevant disciplines] For each discipline: how do they define and operationalize this concept? What methodologies do they use to study it? What are their key findings? What terminology do they use (same concept, different name)? How could their perspective enrich my [your discipline] research? Identify: where disciplines agree, where they fundamentally disagree, and specific papers or scholars who have done cross-disciplinary work on this concept.

I want to study [research question] in [field]. Help me design the study: Constraints: [budget, timeline, access to participants/data] My skills: [what methods I know] Required by: [thesis committee, IRB, journal standards] Design a study that includes: research approach (qualitative/quantitative/mixed) with justification, specific methodology and why it's the best fit, sampling strategy (who, how many, how to recruit), data collection instruments (what to measure and how), data analysis plan (specific techniques), timeline with phases, ethical considerations and IRB requirements, and limitations you're building in from the start (and how to mitigate them). Propose two alternative designs so I can discuss options with my advisor.

I'm creating a survey to measure [construct/variable] for my research on [topic]. Target population: [who's taking it]. Design a survey instrument that includes: 15-25 items measuring [construct], response scale options with recommendation (Likert, semantic differential, etc.), demographic questions relevant to my research, reverse-coded items to check response quality, pilot testing plan, instructions for participants, estimated completion time, and validity considerations (content validity, construct validity). For each item, explain what it measures and why it's included. Flag any questions that might be culturally biased or confusing.

I'm conducting [semi-structured/structured/unstructured] interviews for my [qualitative/mixed methods] research on [topic]. Research questions: [List your RQs] Participants: [who, how many, how recruited] Develop an interview protocol with: opening script (consent, recording, confidentiality), warm-up questions to build rapport, 8-12 core questions mapped to my research questions, follow-up probes for each question (for when respondents give brief answers), closing questions (anything else? member checking), and a debrief script. For each question, explain: what RQ it addresses, what data it's expected to generate, and common pitfalls (leading questions, double-barreled questions). Include timing estimates.

I need help choosing the right statistical test for my research. Research question: [what you're trying to find out] Independent variable(s): [list with type: categorical/continuous, number of levels] Dependent variable(s): [list with type: categorical/continuous] Sample size: [N] Data distribution: [normal/non-normal/unknown] Research design: [between-subjects/within-subjects/mixed] Recommend: the appropriate statistical test with justification, assumptions to check (and how to check them), what to do if assumptions are violated (non-parametric alternatives), effect size measure to report, how to interpret the results in plain English, the specific commands in [R/SPSS/Python] to run the analysis, and how to report results in APA format.

I want to use mixed methods to study [topic]. My research questions require both quantitative and qualitative data. Quantitative RQ: [what you want to measure] Qualitative RQ: [what you want to understand in depth] Constraints: [timeline, budget, access] Design a mixed methods study: recommend the design type (convergent, explanatory sequential, exploratory sequential) with justification, Phase 1 design (methodology, sample, data collection, analysis), Phase 2 design (methodology, sample, data collection, analysis), integration strategy (how quantitative and qualitative findings connect), timeline with phase overlap or sequencing, and sampling strategy (same participants for both phases? different?). Address the philosophical challenges: how do you reconcile positivist and interpretivist paradigms?

Help me write an IRB (Institutional Review Board) application for my research: Study title: [title] Purpose: [brief description] Participants: [who, how many, how recruited] Procedures: [what participants will do] Risks: [potential risks to participants] Benefits: [benefits to participants or society] Draft the application sections: study description (purpose, significance, design), participant information (eligibility, recruitment, compensation), informed consent document (plain language, all required elements), risk assessment and mitigation, data storage and confidentiality plan, vulnerable populations considerations (if applicable), and conflict of interest disclosure. Use the template format from [university/institution if known]. Flag any elements that might require full board review rather than expedited review.

I have a dataset for my research on [topic]. Help me plan the analysis: Dataset: [describe — number of records, variables, source] Research questions: [List RQs] Design an analysis pipeline: data cleaning steps (missing values, outliers, recoding), descriptive statistics to compute first, assumption checks for planned analyses, main analyses mapped to each RQ, post-hoc or follow-up analyses if main analyses are significant, sensitivity analyses to check robustness, and visualization plan (which findings need figures vs tables). For each step, provide the [R/Python/SPSS] code or command. Include decision points: "if X result, proceed with Y; if not, proceed with Z."

Help me interpret these statistical results from my [type] analysis: [Paste statistical output or describe results: - Test used - Test statistic and value - p-value - Effect size - Confidence intervals - Sample size] Context: my hypothesis was [state hypothesis]. Explain: what these numbers mean in plain English (not just "significant" or "not significant"), whether the results support or refute my hypothesis, the practical significance (effect size interpretation), the confidence interval meaning, any caveats or limitations of this specific result, and how to report these results in APA format with proper notation. Also suggest: what additional analyses might strengthen this finding, and how to discuss this result in the context of [previous research findings].

I'm coding qualitative data (interview transcripts/field notes/documents) for my research on [topic]. Research questions: [List RQs] Methodological approach: [grounded theory/thematic analysis/content analysis/phenomenological] Help me create: a coding strategy (deductive from theory, inductive from data, or both), initial code categories based on my RQs and theoretical framework, a codebook template with: code name, definition, inclusion criteria, exclusion criteria, and example quote, guidelines for when to create new codes vs merge existing ones, inter-coder reliability plan (if applicable), and a process for moving from codes to themes to theory. Show an example of coding one sample passage through all three levels.

My dataset has missing data. Help me handle it properly: Dataset: [describe — variables, sample size, source] Missing data pattern: [which variables are affected, roughly what percentage] Likely reason for missingness: [random, systematic, or unknown] Analyze: what type of missing data mechanism is this likely? (MCAR, MAR, MNAR), is the percentage of missingness acceptable for my analysis? Should I use: listwise deletion, pairwise deletion, mean/median imputation, regression imputation, multiple imputation, or maximum likelihood estimation? For my recommended approach: explain why it's appropriate for my specific situation, show the [R/Python/SPSS] code to implement it, describe how to report the missing data handling in my paper, and explain what sensitivity analyses to run to ensure results aren't driven by the imputation method.

I need to create figures and tables for my research paper on [topic]. My key results: [Describe results that need visualization] Target journal: [journal name and style guide] For each result, recommend: the best visualization type and why (bar chart, scatter plot, box plot, etc.), what to include and what to leave out, axis labels, legends, and annotations, color scheme that works in print and for color-blind readers, and the [R ggplot2/Python matplotlib/other] code to create it. For tables: recommend which results belong in tables vs figures, create APA-format table templates, and note what to include in table notes. Follow [journal] formatting guidelines.

I need a power analysis for my planned study: Study design: [describe — experimental, correlational, survey, etc.] Analysis planned: [specific statistical test] Expected effect size: [small/medium/large, or specific d/r/f value] Basis for effect size estimate: [previous studies, pilot data, or minimum meaningful effect] Desired power: [typically .80 or .90] Alpha level: [typically .05] Calculate: the minimum required sample size, sensitivity analysis (what effects can I detect with [realistic N]?), how sample size changes with different power levels and effect sizes, practical recommendations (recruit more than minimum to account for attrition), and the [G*Power/R/Python] commands to reproduce this calculation. If my realistic sample size is smaller than needed, suggest: alternative designs, different analyses, or ways to increase power without more participants.

Help me structure a research paper for [target journal/conference] on [topic]. Research question: [RQ] Methodology: [brief description] Key findings: [main results] Contribution: [what's new about this work] Create a detailed outline for: Abstract (structured: background, methods, results, conclusions — 250 words), Introduction (problem statement, significance, literature gap, RQ, paper structure), Literature Review (themes, not source-by-source), Methodology (design, participants, procedures, analysis), Results (organized by RQ, with figure/table placement notes), Discussion (interpretation, comparison to prior work, implications, limitations), and Conclusion (summary, contributions, future research). For each section, provide: the key argument or purpose, approximate word count, and pitfalls to avoid.

Write a research abstract for my paper: Title: [paper title] Research question: [RQ] Method: [briefly describe] Key findings: [main results with numbers] Contribution: [why this matters] Target journal: [journal name] Word limit: [typically 150-300] The abstract should: state the problem and why it matters (1-2 sentences), describe the methodology (1-2 sentences), present key findings with specific results (2-3 sentences), explain the significance and implications (1-2 sentences), and include 4-6 keywords for indexing. Write three versions: a structured abstract (with labeled sections), a narrative abstract (flowing prose), and a conference abstract (slightly more accessible/engaging). All must stay within the word limit.

I received peer review comments on my manuscript and need to write a response. Here are the reviewer comments: Reviewer 1: [Paste comments] Reviewer 2: [Paste comments] Editor: [Paste comments] Help me draft a response letter that: addresses every single comment (number them), is respectful and professional even when I disagree, clearly indicates what changes I made (with page/line numbers), explains my reasoning when I decline a suggestion, includes new text where I've added or revised content, and thanks reviewers for constructive feedback. For each response: categorize as "accepted and revised," "partially addressed," or "respectfully declined with explanation." Create a change summary table at the top.

Improve the clarity and readability of this academic writing while maintaining scholarly tone: [Paste paragraph or section] Specifically: shorten sentences over 30 words, replace jargon with clearer alternatives (or define it on first use), eliminate hedging that weakens claims without adding nuance, fix passive voice where active is clearer, ensure each paragraph has one clear point, improve transitions between paragraphs, and remove filler phrases ("it is important to note that," "it should be mentioned that"). Show the revised version and explain each change. Rate the original on readability (1-10) and the revision.

Help me identify target journals for my research paper: Topic: [describe your research] Methodology: [type] Discipline: [primary field, plus interdisciplinary connections] Key findings: [brief summary] Target audience: [who should read this] Career context: [PhD student/postdoc/professor — impacts journal strategy] Suggest 5-7 journals ranked by fit, for each providing: journal name and publisher, scope and typical papers they publish, impact factor and ranking in field, acceptance rate (estimated), typical review timeline, open access status and APC costs, and why my paper would be a good fit (or stretch). Include 2 "reach" journals and 2 "safety" journals. Suggest an order to submit (don't start with your top choice — start with your second choice for feedback).

Help me draft a grant proposal for [funding body: NSF/NIH/foundation/university]. Project: [title and description] Amount requested: [budget] Duration: [timeline] PI qualifications: [your background] Draft these sections: specific aims/objectives (1 page), significance and innovation (why this matters and what's new), research plan (approach, timeline, milestones), preliminary data (if any — how to present it compellingly), budget justification (how funds will be used), broader impacts/knowledge mobilization, and PI qualifications and research environment. Follow [funding body] formatting requirements. For each section, note what reviewers specifically look for and common reasons proposals are rejected.

Help me create a realistic timeline for my research project: Project: [thesis/dissertation/paper/grant project] Start date: [date] Deadline: [date] Milestones required by institution: [proposal defense, IRB, data collection, etc.] Other commitments: [teaching, coursework, job, etc.] Create a Gantt-style timeline that: breaks the project into phases with tasks, accounts for realistic durations (not best-case scenarios), builds in buffer time for delays (things always take longer than planned), parallelizes activities where possible, identifies the critical path, accounts for external dependencies (IRB approval, participant recruitment, committee availability), and includes "check-in" points to assess if I'm on track. Flag the phases where students typically fall behind and suggest how to avoid it.

I have [number] references collected for my research on [topic]. They're currently [disorganized/in one folder/scattered]. Help me create an organization system: Research questions: [List RQs] Create: a folder/tag structure based on themes (not chronology), a reading priority system (which papers to read first/deep/skim), a note-taking template for each paper (citation, summary, methodology, key findings, quotes, relevance to my RQ, connections to other papers), a system for tracking which papers I've read vs skimmed vs unread, and a strategy for staying current with new publications. Recommend a reference management tool [Zotero/Mendeley/EndNote] setup optimized for my workflow. Include: tag suggestions, smart folder configurations, and annotation conventions.

Help me write a research proposal for my [thesis/dissertation] committee: Topic: [your research topic] Research questions: [List RQs] Proposed methodology: [brief description] Committee expectations: [any specific requirements] Draft a proposal that includes: introduction and problem statement, literature review outline (key themes you'll cover), theoretical/conceptual framework, methodology (design, participants, procedures, analysis), expected contributions (to theory and practice), timeline, and potential limitations. Write in a way that: demonstrates you understand the field, shows your methodology is sound, convinces the committee this is feasible, and preemptively addresses likely committee questions. Include a list of likely committee questions with suggested responses.

Help me develop the theoretical framework for my research on [topic]. My research question: [RQ] Key variables/concepts: [list them] Discipline: [your field] Theories I'm considering: [list any theories you've encountered] Help me: identify 2-3 theories that could frame my research, explain each theory's core propositions, show how each theory relates to my specific variables, evaluate which theory (or combination) best fits my RQ, create a conceptual framework diagram description showing relationships between variables, articulate hypotheses derived from the framework, and anticipate how reviewers might challenge my framework choice. Distinguish between theoretical framework (existing theory) and conceptual framework (your specific model).

I'm presenting my research at [context: conference/thesis defense/lab meeting]. Details: Audience: [who, their expertise level] Time: [duration, including Q&A] Topic: [what I'm presenting] Key findings: [main results] Create: a slide-by-slide outline with content and timing, speaker notes for each slide (what to say, not just what to show), a "story arc" that makes the research compelling (not just informative), anticipated questions with prepared answers (especially the tough ones), tips for handling: "why didn't you..." questions, hostile questions, and "I don't understand" reactions, and a practice checklist. For a defense specifically: add common defense questions by committee type (methodologist, theorist, external).

I'm conducting a systematic review on [topic]. Help me create a PRISMA-compliant protocol: Research question (PICO/PEO format): [P: population, I/E: intervention/exposure, C: comparison, O: outcome] Develop: inclusion and exclusion criteria (specific and testable), database search strategy with search strings for [list databases], screening process (title/abstract screening, full-text review), quality assessment tool selection and criteria, data extraction form (what to extract from each study), synthesis strategy (narrative, meta-analysis, or both), plan for assessing risk of bias, and PRISMA flow diagram description. Include: a pilot testing plan for the screening criteria and inter-rater reliability process.

I'm writing a case study analysis for [purpose: academic paper/thesis/course assignment]. Case: [describe the case — organization, event, person, etc.] Research question: [what are you investigating through this case?] Theoretical lens: [theory you're using to analyze the case] Help me structure the case study: case description (relevant background, chronology of events), analytical framework (how the theory applies to this case), analysis by theme or chronology (connecting evidence to theory), findings (what the case reveals about the broader phenomenon), discussion (how this case compares to other cases or prior research), limitations (what this case can and cannot tell us), and implications (for theory, practice, and future research). For each section, suggest what evidence to include and what level of detail is appropriate.

I'm conducting a content analysis of [material: social media posts/news articles/documents/etc.] to study [research question]. Sample: [what material, time period, selection criteria] Approach: [quantitative content analysis/qualitative content analysis/critical discourse analysis] Help me design: sampling strategy (universe, sampling frame, sample selection), unit of analysis (word, sentence, paragraph, article, etc.), coding scheme with categories and definitions, coding sheet/template, inter-coder reliability plan and acceptable thresholds, analysis procedure (frequency counts, cross-tabulation, thematic patterns), and reporting format. Provide 5 sample codes with definitions, examples, and non-examples. Include decision rules for ambiguous cases.

I need to write a research memo documenting my analytical thinking. Context: What I'm working on: [phase of research] Data I'm looking at: [describe the data or observations] What I'm noticing: [patterns, surprises, connections, contradictions] Questions arising: [things I'm wondering about] Help me write a structured memo that: documents the date and context, describes the pattern or observation that triggered this memo, connects it to existing theory or prior memos, generates hypotheses or questions to pursue, identifies what data I need to look at next, and notes any methodological decisions or changes I'm considering. Maintain a reflective, exploratory tone — this is thinking-in-progress, not polished writing.

I'm validating a measurement instrument (scale/questionnaire/assessment) for my research. Instrument: [describe — what it measures, number of items, response format] Original context: [where it was developed and validated] My context: [different population, language, culture, etc.] Design a validation study: content validity (expert review panel plan), face validity (target population feedback), construct validity (confirmatory factor analysis plan), convergent validity (what to correlate with), discriminant validity (what it should NOT correlate with), criterion validity (if a gold standard exists), reliability (internal consistency and test-retest plan), and cross-cultural adaptation process (if translating). Specify: sample sizes needed for each validation step, statistical tests and acceptable thresholds, and how to report validation results. Include a decision framework: when is the instrument "valid enough" to use?

I need to assess the ethical dimensions of my planned research: Study: [describe the study] Participants: [who and how recruited] Procedures: [what participants will experience] Data: [what you're collecting and how stored] Conduct an ethics assessment covering: informed consent (is it truly informed and voluntary?), risk-benefit analysis (do benefits justify the risks?), privacy and confidentiality (how data is protected), vulnerable populations (are any participants vulnerable? how to protect them?), deception (is any deception necessary? justified?), power dynamics (researcher-participant relationship), data management (storage, access, retention, destruction), dissemination (could publishing results harm participants?), and cultural sensitivity (is the research respectful of cultural contexts?). For each area, rate risk as low/medium/high and suggest specific mitigation strategies.

My research paper has been accepted and I need to prepare supplementary materials. The paper covers [topic] with [methodology]. Available supplementary material: [List what you could include: additional analyses, full datasets, code, instruments, extended tables, etc.] Help me organize supplementary materials: decide what belongs in supplementary vs the main paper, create a logical structure with clear labeling (Appendix A, B, C...), write brief introductions for each supplement explaining what it contains, format tables and figures to be self-contained, ensure all supplements are referenced in the main text, create a README if sharing code or data, and address data sharing requirements for [journal/funder]. Follow [journal] supplementary material guidelines.