30 Research Question Examples for Qualitative, Quantitative, and Mixed-Methods Studies

A good research question names who or what you will study, what you want to understand or measure, and how narrow the project will be. The examples below are built for three common designs: qualitative, quantitative, and mixed methods.

Use them as models, not as scripts. Swap in your own population, setting, variable, outcome, intervention, or time frame so the question fits the data you can actually collect.

How to use these research question examples

The fastest way to choose the right example is to match the question to the kind of evidence your study needs.

A reusable structure looks like this:

Population or setting + phenomenon, variable, or intervention + purpose + feasible scope

For example:

• Too broad: “How does technology affect students?”

• Better qualitative version: “How do first-year university students describe using AI writing tools when revising essays in an introductory composition course?”

• Better quantitative version: “Is weekly use of AI writing tools associated with final essay scores among first-year composition students?”

• Better mixed-methods version: “Is AI writing-tool use associated with final essay scores, and how do students explain the ways these tools shape their revision decisions?”

A strong research question should pass five checks:

1. It is answerable with the proposed data. Do not ask about “impact” if you only have interview data about perceptions.

2. It is narrow enough for the assignment. One population, one setting, and one main outcome or phenomenon are usually enough.

3. It matches the design. Qualitative questions should not require statistical proof; quantitative questions should not depend on vague impressions.

4. It is ethically and practically feasible. Sensitive populations, medical records, minors, and workplace data may require permissions you do not have.

5. It fits the word count and timeline. A 2,500-word class paper cannot answer a national policy question with six variables.

If you want a fuller process before choosing your wording, see this guide on how to create a research question.

10 qualitative research question examples

Qualitative research questions explore meaning, experience, process, identity, interpretation, or decision-making. They work best when the researcher wants depth rather than measurement.

A useful qualitative question usually names:

• Population: Who is being studied?

• Phenomenon: What experience, process, or meaning is being explored?

• Method: Interviews, focus groups, observations, document analysis, or another qualitative method.

• Scope: A course, clinic, workplace, community, program, or other bounded setting.

For more detail on the structure, read Otio’s guide to what makes a qualitative research question.

1. Student experiences of feedback

Research question: How do first-year university students describe using instructor feedback to revise their academic writing?

• Population: First-year university students

• Phenomenon: Use of instructor feedback

• Method: Semi-structured interviews

• Scope: One writing course, department, or first-year program

This question works because it does not try to measure whether feedback “improves” writing. It asks how students interpret and use feedback, which fits interview data.

2. Remote-work boundaries

Research question: How do early-career employees experience the negotiation of work-life boundaries in fully remote teams?

• Population: Early-career remote employees

• Phenomenon: Boundary negotiation

• Method: Interviews or focus groups

• Scope: One industry, company type, or occupational group

This version is stronger than “How does remote work affect employees?” because it names a specific experience: managing boundaries.

3. Caregiver decision-making

Research question: How do family caregivers describe deciding whether to use home-based services for older relatives with mobility limitations?

• Population: Family caregivers

• Phenomenon: Care-service decision-making

• Method: Narrative interviews

• Scope: One local service system or community organization

This question is suited to narrative interviews because it asks participants to explain a decision process over time.

4. Nursing-student simulation

Research question: How do nursing students perceive the role of simulation debriefings in preparing them for clinical placements?

• Population: Nursing students

• Phenomenon: Debriefing experiences

• Method: Focus groups

• Scope: One nursing program or cohort

The word “perceive” signals that the study is about student interpretation, not an objective test of clinical performance.

5. Public-library access

Research question: How do adult immigrants describe using public libraries to support language learning and community participation?

• Population: Adult immigrants

• Phenomenon: Library use for language learning and participation

• Method: Interviews and observations

• Scope: One library network or municipality

This question gives the researcher room to explore formal services, informal practices, barriers, and social meanings.

6. Small-business cybersecurity

Research question: How do owners of small businesses make sense of cybersecurity risks when choosing digital payment systems?

• Population: Small-business owners

• Phenomenon: Risk interpretation and technology decisions

• Method: Interviews

• Scope: One business sector, such as food service or retail

“Make sense of” is useful in qualitative research because it points to interpretation, assumptions, and decision logic.

7. Patient trust in telehealth

Research question: How do patients describe the factors that build or weaken trust during primary-care telehealth visits?

• Population: Primary-care telehealth patients

• Phenomenon: Trust formation

• Method: Interviews

• Scope: One clinic, patient group, or care context

This question is narrow enough to guide an interview protocol but open enough to capture unexpected themes.

8. First-generation doctoral students

Research question: How do first-generation doctoral students describe developing a sense of belonging in their academic departments?

• Population: First-generation doctoral students

• Phenomenon: Belonging

• Method: Phenomenological interviews

• Scope: One discipline, institution, or doctoral program type

This is a good fit for phenomenological research because it centers lived experience.

9. Teacher adoption of classroom technology

Research question: How do secondary-school teachers explain their decisions to continue or abandon a newly introduced learning platform?

• Population: Secondary-school teachers

• Phenomenon: Adoption and abandonment decisions

• Method: Interviews and document review

• Scope: One school district or platform rollout

This question avoids the vague phrasing “teacher attitudes toward technology” and instead studies a concrete decision.

10. Community responses to climate adaptation

Research question: How do residents describe the fairness of proposed flood-prevention measures in their neighborhoods?

• Population: Residents in flood-risk areas

• Phenomenon: Perceived fairness

• Method: Focus groups

• Scope: One neighborhood, municipality, or planning process

Fairness is a good qualitative construct when the goal is to understand values, tradeoffs, and local concerns.

10 quantitative research question examples

Quantitative research questions measure variables, relationships, differences, predictions, or intervention effects. They require data that can be counted, scored, compared, or modeled.

A useful quantitative question usually names:

• Population: Who or what is measured?

• Predictor or independent variable: The possible cause, condition, group, or exposure.

• Outcome or dependent variable: The result being measured.

• Method: Survey, experiment, quasi-experiment, observational study, cohort study, or analysis of records.

• Scope: One course, clinic, organization, school district, or time frame.

If you need more models, Otio has a separate set of quantitative research examples and templates.

11. Study habits and achievement

Research question: What is the relationship between weekly study hours and examination scores among first-year biology students?

• Population: First-year biology students

• Variables: Weekly study hours and examination scores

• Method: Correlational survey plus grade data

• Scope: One biology course

This question can be answered with numeric data. It does not claim that study hours cause higher scores unless the design supports that claim.

12. Sleep and academic performance

Research question: Does average nightly sleep duration predict semester GPA among undergraduate students?

• Population: Undergraduate students

• Predictor: Average nightly sleep duration

• Outcome: Semester GPA

• Method: Cross-sectional survey or longitudinal tracking

• Scope: One institution

“Predict” suggests a statistical model, such as regression. It does not automatically prove causation.

13. Telehealth and appointment access

Research question: Does offering telehealth reduce the average time patients wait for a primary-care appointment?

• Population: Primary-care patients

• Variables: Visit format and appointment wait time

• Method: Comparative observational study

• Scope: One clinic or clinic network

This question is practical because wait time can be defined clearly, such as days between request and appointment.

14. Training and employee errors

Research question: Is completion of a cybersecurity training module associated with fewer simulated phishing errors among new employees?

• Population: New employees

• Predictor: Training completion

• Outcome: Simulated phishing errors

• Method: Quasi-experiment or observational comparison

• Scope: One organization

The phrase “associated with” is safer than “causes” if employees were not randomly assigned to training.

15. Exercise and stress

Research question: What is the association between weekly moderate-to-vigorous exercise and perceived stress among graduate students?

• Population: Graduate students

• Variables: Exercise frequency and perceived-stress score

• Method: Survey-based correlational study

• Scope: One graduate school

This question works well when both constructs can be measured with survey items or validated scales.

16. Class size and participation

Research question: Does class size affect the frequency of student participation in undergraduate seminar discussions?

• Population: Undergraduate seminar classes

• Predictor: Class size

• Outcome: Participation frequency

• Method: Structured observation

• Scope: One department

This question needs a clear participation measure, such as number of voluntary comments per session.

17. Food insecurity and concentration

Research question: Is food-insecurity status associated with self-reported concentration difficulties among community-college students?

• Population: Community-college students

• Variables: Food-insecurity status and concentration difficulties

• Method: Anonymous survey

• Scope: One college

Because the topic is sensitive, anonymity and ethical review matter as much as the wording.

18. Medication adherence intervention

Research question: Does text-message medication support improve adherence compared with usual care among adults managing hypertension?

• Population: Adults with hypertension

• Intervention: Text-message medication support

• Outcome: Medication adherence

• Method: Randomized or quasi-experimental comparison

• Scope: One clinic

This is an intervention question, so it should include a comparison group and a measurable outcome.

19. Social-media use and body image

Research question: Does daily social-media exposure predict body-image dissatisfaction among adolescents?

• Population: Adolescents

• Predictor: Daily social-media exposure

• Outcome: Body-image dissatisfaction score

• Method: Survey with regression analysis

• Scope: One school district

This question should be handled carefully because it involves minors and a potentially sensitive psychological outcome.

20. Internship experience and employment

Research question: Does completing a paid internship increase the likelihood of securing full-time employment within six months of graduation?

• Population: Recent graduates

• Predictor: Paid internship completion

• Outcome: Full-time employment status

• Method: Cohort study or retrospective survey

• Scope: One degree program

This question is stronger than “Do internships help students?” because it defines the internship type, outcome, and time frame.

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10 mixed-methods research question examples

Mixed-methods research questions combine measurement with explanation. They are useful when numbers alone are too thin and interviews alone are too narrow.

Most mixed-methods studies use one of three broad logics:

• Explanatory sequential: Collect quantitative data first, then use qualitative data to explain the results.

• Exploratory sequential: Explore qualitatively first, then test or measure the themes quantitatively.

• Convergent: Collect qualitative and quantitative data in parallel, then compare or integrate findings.

The examples below use the common structure:

Quantitative pattern + qualitative explanation + integrated purpose

21. Online-learning engagement

Research question: What factors are associated with engagement in online courses, and how do students explain the behaviors behind high or low engagement?

• Quantitative phase: Engagement metrics and survey

• Qualitative phase: Student interviews

• Population: Undergraduate students

• Scope: One online program

This is a good explanatory sequential question: first identify engagement patterns, then interview students who represent different patterns.

22. Nursing retention

Research question: Which workplace factors predict intent to leave among hospital nurses, and how do nurses describe the experiences shaping that intent?

• Quantitative phase: Retention or workplace-climate survey

• Qualitative phase: Interviews

• Population: Hospital nurses

• Scope: One health system

The quantitative strand identifies predictors; the qualitative strand explains what those factors feel like in practice.

23. Small-business technology adoption

Research question: How widely do small businesses adopt artificial-intelligence tools, and how do owners explain barriers to sustained use?

• Quantitative phase: Adoption survey

• Qualitative phase: Owner interviews

• Population: Small businesses

• Scope: One region or industry

This question separates initial adoption from sustained use, which often reveals different barriers.

24. Teacher professional development

Research question: Does participation in a professional-development program relate to changes in instructional confidence, and how do teachers describe applying the training?

• Quantitative phase: Pre/post confidence scale

• Qualitative phase: Interviews or classroom observations

• Population: Participating teachers

• Scope: One district

This question works when the study needs both a measurable change and examples of classroom application.

25. Telehealth satisfaction

Research question: How do patient demographics and visit characteristics relate to telehealth satisfaction, and why do patients report different levels of satisfaction?

• Quantitative phase: Satisfaction survey

• Qualitative phase: Follow-up interviews

• Population: Telehealth patients

• Scope: One clinic

This design can explain why two groups with similar access report different satisfaction levels.

26. First-generation student support

Research question: Which campus-support services are associated with first-generation students’ academic persistence, and how do students describe the services that help or fail them?

• Quantitative phase: Institutional records or survey

• Qualitative phase: Interviews

• Population: First-generation undergraduate students

• Scope: One institution

The qualitative strand prevents the study from treating “support service use” as a simple yes-or-no variable.

27. Climate-risk communication

Research question: How does exposure to flood-risk information relate to residents’ preparedness intentions, and how do residents interpret the credibility and usefulness of that information?

• Quantitative phase: Preparedness survey

• Qualitative phase: Focus groups

• Population: Residents in flood-risk areas

• Scope: One municipality

This question is well suited to a convergent or explanatory design because risk communication depends on both exposure and interpretation.

28. Public-library programming

Research question: Which factors predict attendance at adult literacy programs, and how do attendees describe the program features that influence continued participation?

• Quantitative phase: Attendance and demographic data

• Qualitative phase: Interviews

• Population: Adult literacy-program participants

• Scope: One library system

The quantitative data shows who attends; interviews explain why people keep coming or stop.

29. Work-from-home productivity

Research question: Is perceived productivity associated with specific remote-work practices, and how do employees explain the practices that support or hinder their work?

• Quantitative phase: Employee survey

• Qualitative phase: Interviews

• Population: Remote employees

• Scope: One organization

This question avoids treating remote work as one uniform condition. It studies specific practices, such as meeting norms, communication channels, or schedule flexibility.

30. Health-app adherence

Research question: Does use of a mobile health app relate to improved exercise adherence, and how do users describe the app features that influence continued use?

• Quantitative phase: Usage and adherence data

• Qualitative phase: User interviews

• Population: Adult app users

• Scope: One health program

The mixed-methods design is useful here because app usage logs can show behavior, while interviews can explain motivation, friction, and abandonment.

How to choose and narrow your research question

Start with the decision your study must make: are you trying to understand an experience, measure a relationship, or connect a pattern with an explanation?

Choose qualitative research when the main gap concerns how people experience, interpret, explain, or navigate a phenomenon. Good qualitative topics often involve identity, decision-making, trust, fairness, belonging, adaptation, or meaning.

Choose quantitative research when the study needs to estimate prevalence, compare groups, test an association, predict an outcome, or evaluate an intervention. Good quantitative topics require variables that can be defined before data collection begins.

Choose mixed methods when one kind of evidence is not enough. Use mixed methods when numerical results need explanation, qualitative themes need broader testing, or the research problem has complementary “what” and “why” parts.

A quick narrowing sequence

Use this sequence when your topic is still too broad:

1. Name the broad topic. Example: technology and learning.

2. Choose one population. First-year university students.

3. Choose one setting. Introductory composition courses.

4. Choose one phenomenon or outcome. Revision decisions, essay scores, confidence, or feedback use.

5. Choose one data source. Interviews, survey responses, assignment grades, LMS data, or observations.

6. Add a time frame or boundary. One semester, one course, one department, or one program.

7. Match the design. Exploration, measurement, or both.

That process turns a vague topic into something researchable:

• Too broad: “What is the impact of technology on education?”

• Qualitative: “How do first-year composition students describe using AI writing tools when revising essays during one semester?”

• Quantitative: “Is weekly AI writing-tool use associated with final essay scores among first-year composition students in one course?”

• Mixed methods: “Is weekly AI writing-tool use associated with final essay scores, and how do students explain the role of these tools in their revision decisions?”

Check alignment before drafting

Before writing the proposal, check that every part of the study points at the same construct.

A common failure is asking a causal question with non-causal data. For example, “Does social media cause anxiety?” requires a design that can support causal inference. If the study only uses a one-time survey, a safer question is: “What is the association between daily social-media use and self-reported anxiety among undergraduate students?”

Another common failure is mixing too many populations into one question. “How do teachers, parents, and students perceive online learning?” may be feasible for a large study, but it is often too much for a class paper. A narrower version would focus on one group: “How do secondary-school teachers describe challenges in sustaining student participation during online lessons?”

If the question depends on literature you are still sorting through, use a source-and-note workflow before finalizing the wording. A research workspace such as Otio can help organize PDFs, web sources, notes, and chats in one project library while comparing definitions, variables, and methods across studies.

For a broader methods overview, see research methodology types and how to choose the right one. If you are building the full design after choosing the question, this guide to research design examples for thesis writers gives more examples of variables, methods, and scope.

FAQ

Q: Can one study have more than one research question?
A: Yes. A study can include one primary question and several secondary questions, but each should serve the same research problem and remain feasible for the available sample, data, and timeline.

Q: Should a research question include a hypothesis?
A: Quantitative studies often pair research questions with testable hypotheses. Qualitative studies usually use open-ended questions rather than predictions, while mixed-methods studies may use hypotheses for the quantitative strand and exploratory questions for the qualitative strand.

Q: What makes a research question too broad?
A: A question is usually too broad when it covers multiple populations, settings, outcomes, or causes that cannot be studied with the available resources. Add a specific population, context, construct, and time frame to make it manageable.

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Related reading

• How To Create A Research Question In 6 Simple Steps

• What Is A Qualitative Research Question

• 28 Best Quantitative Research Examples & Templates for Thesis Writers

• 25 Research Design Examples for Thesis Writers