What is a qualitative research methodology in academia?

Qualitative research is one of the two fundamental approaches to academic inquiry. Where quantitative research measures, counts, and tests hypotheses using numerical data, qualitative research explores, interprets, and builds understanding using words, images, and observations.

For researchers in the social sciences, education, health sciences, business, and humanities, qualitative methods are often the most appropriate way to investigate complex human phenomena. Why do patients choose to discontinue treatment? How do first-generation university students experience the transition to postgraduate study? What meaning do teachers assign to professional development programmes? These are questions that surveys and statistical tests cannot adequately answer. They require depth, context, and the ability to capture the richness of human experience.

This guide covers the foundations of qualitative research methodology: what it is, when to use it, the main research designs, data collection and analysis methods, how to establish rigour, and how to write a qualitative methodology section that satisfies reviewers.

What Qualitative Research Is (and Is Not)

Qualitative research is a systematic approach to understanding social phenomena from the perspective of the people involved. It collects non-numerical data, primarily through interviews, observations, and document analysis, and analyses that data through coding, categorisation, and interpretation.

The philosophical foundation is interpretivism (also called constructivism). This is the position that reality is not a single, fixed, measurable thing, but is instead socially constructed and experienced differently by different people. A qualitative researcher does not assume there is one truth to discover. They assume there are multiple perspectives to understand.

Qualitative research is not just “research without numbers.” It is not a fallback when you cannot get a large enough sample for statistical analysis. It is not easier than quantitative research, it is simply different. It has its own standards of rigour, its own traditions, and its own criteria for quality. Treating qualitative research as the soft alternative to “real” (quantitative) research is a misunderstanding that persists in some disciplines but is increasingly outdated.

When to Use Qualitative Methods

Qualitative methods are appropriate when your research question asks about experiences, perceptions, processes, or meanings. They are also appropriate when the topic is under-researched and you are exploring new ground rather than testing existing theory, when the context matters and stripping it away (as quantitative designs often do) would lose important information, when you need to understand the “why” behind patterns observed in quantitative data, and when you are studying sensitive topics where trust and rapport between researcher and participant are essential.

Qualitative methods are less appropriate when your question requires measurement, comparison of group means, or generalisation to a large population. If you need to know how many, how much, or whether a relationship is statistically significant, you need quantitative methods. For guidance on choosing between approaches, see our post on qualitative vs quantitative research.

The Five Main Qualitative Research Designs

Qualitative research is not a single method. It is a family of approaches, each with a different purpose and analytical tradition. The five most common designs in academic research are outlined below.

Phenomenology explores the lived experience of individuals who share a common phenomenon. The goal is to describe what the experience is like and what meaning participants assign to it. A phenomenological study might explore the experience of burnout among junior doctors, or the experience of returning to education after a career break. Data is typically collected through in-depth, semi-structured interviews with 5 to 25 participants. Analysis involves identifying significant statements, grouping them into meaning units, and constructing a textural and structural description of the experience.

Grounded theory aims to develop a theory that is grounded in data rather than testing a pre-existing theory. The researcher collects data (usually through interviews), codes it, and builds theory iteratively through constant comparison. New data collection is guided by the emerging theory. Sample sizes are typically 20 to 30 participants, though data collection continues until theoretical saturation is reached. Grounded theory is particularly useful when no adequate theory exists to explain the phenomenon you are studying.

Ethnography studies a cultural group or community by immersing the researcher in that group’s environment over an extended period. The researcher observes, participates, takes field notes, conducts informal interviews, and collects artefacts. Ethnographic studies can last months or years. The output is a thick description of the culture, its norms, its practices, and the meanings its members assign to their actions. Ethnography is common in anthropology, sociology, and education.

Case study research investigates a bounded system (a person, a group, an organisation, an event) in depth and within its real-world context. Case studies can use multiple data sources: interviews, observations, documents, and sometimes quantitative data. They are particularly useful for studying complex, context-dependent phenomena. A case study might examine how a specific university implemented a new teaching policy, or how a particular company responded to a crisis. Single-case and multiple-case designs are both common.

Narrative inquiry focuses on the stories people tell about their experiences. The researcher collects and analyses personal narratives, life histories, or biographical accounts. The emphasis is on how people construct meaning through storytelling, and on the temporal sequence of events as experienced by the narrator. Narrative inquiry is used in education, nursing, psychology, and the humanities.

Data Collection Methods

The primary data collection methods in qualitative research are interviews, focus groups, observation, and document analysis. Most qualitative studies use one or two of these in combination.

Interviews are the most common method. Semi-structured interviews use a topic guide with predetermined questions but allow the researcher to probe deeper when interesting responses emerge. Unstructured interviews are more open-ended and conversational. Interviews typically last 45 to 90 minutes and are audio-recorded and transcribed verbatim. The quality of your interview data depends heavily on your skill as an interviewer: your ability to build rapport, ask follow-up questions, listen actively, and create a safe space for honest responses.

Focus groups are group interviews, typically with 6 to 10 participants, moderated by the researcher. They are useful for exploring how people interact and negotiate meaning in a social setting. The group dynamic can produce insights that individual interviews do not. However, dominant participants can suppress minority views, and sensitive topics may not be discussed openly.

Observation can range from participant observation (where the researcher is embedded in the setting) to non-participant observation (where the researcher observes without participating). Field notes are the primary data output. Observation is essential in ethnographic research and useful in case studies.

Document analysis involves examining existing texts: policy documents, meeting minutes, social media posts, diaries, letters, or media reports. Documents provide context and can corroborate or challenge findings from interviews and observations.

Data Analysis: Coding and Thematic Analysis

The most widely used analytical approach in qualitative research is thematic analysis. The process involves six stages: familiarisation (reading and re-reading your data), initial coding (labelling meaningful segments of text), generating themes (grouping codes into broader themes), reviewing themes (checking that themes are supported by the data), defining themes (naming each theme and writing a description), and writing up (integrating themes into a coherent narrative).

Coding can be done manually (using highlighters and margin notes on printed transcripts) or with software. NVivo, ATLAS.ti, and MAXQDA are the most commonly used qualitative data analysis software packages. They do not analyse your data for you. They organise it. The analytical thinking is still yours.

Other analytical approaches include constant comparative analysis (used in grounded theory), interpretive phenomenological analysis (IPA, used in phenomenological studies), discourse analysis (examining how language constructs meaning), and content analysis (systematically categorising text). The choice of analytical approach should align with your research design and philosophical position.

Establishing Rigour in Qualitative Research

Qualitative research does not use the same criteria for quality as quantitative research. Instead of validity and reliability, qualitative researchers use Lincoln and Guba’s four criteria: credibility, transferability, dependability, and confirmability.

Credibility (the qualitative equivalent of internal validity) is established through prolonged engagement with participants, triangulation (using multiple data sources or methods), member checking (sharing findings with participants for verification), and peer debriefing (discussing your analysis with a colleague).

Transferability (the equivalent of external validity) is not about statistical generalisation. It is about providing enough thick description of the context, participants, and setting that readers can judge whether the findings might apply to their own context.

Dependability (the equivalent of reliability) is established through an audit trail: a detailed record of your research process, decisions, and analytical steps that would allow another researcher to follow your logic.

Confirmability (the equivalent of objectivity) is about demonstrating that your findings are grounded in the data rather than your personal biases. Reflexivity, where you explicitly acknowledge and discuss your own positionality and how it may have influenced the research, is the primary tool here.

Writing the Qualitative Methodology Section

The methodology section is one of the most scrutinised parts of any qualitative paper. Reviewers check whether your design is appropriate, whether you have justified your choices, and whether your procedures are described in enough detail for another researcher to understand (and potentially replicate) your approach.

A strong qualitative methodology section includes your philosophical position and justification for using qualitative methods, the specific research design (phenomenology, grounded theory, etc.) and why you chose it, your sampling strategy and how participants were recruited, a description of your data collection methods and instruments (including your interview guide), your data analysis approach (with enough detail to show how you moved from raw data to themes), how you established rigour (which of the four criteria you addressed and how), and any ethical considerations (informed consent, anonymity, data storage).

Clarity is critical. If the reviewer cannot follow your methodology, they cannot evaluate your study. For non-native English speakers, complex procedures require precise language, and this is where professional editing makes the biggest difference.

Submitting a qualitative research paper? PM Proofreading’s journal manuscript editing service ensures your methodology section and full manuscript are clear, precise, and publication-ready. Every order includes tracked changes and a free language editing certificate. Upload your manuscript and get a quote.

Further Reading

• Qualitative vs Quantitative Research: Key Differences Explained
• How to Conduct a Systematic Literature Review
• How to Structure and Write a Good PhD Research Proposal
• How to Write an Effective Introduction Section of a Research Paper

Frequently Asked Questions

What is the difference between phenomenology and grounded theory?

Phenomenology explores the lived experience of a phenomenon. It asks: “What is it like to experience X?” Grounded theory aims to develop a new theory from data. It asks: “What theory explains the process of X?” Phenomenology describes experience. Grounded theory builds explanatory models. The data collection methods overlap (both use interviews), but the analytical approach and the output are different.

How many participants do I need for a qualitative study?

There is no fixed number. Most qualitative studies involve 10 to 50 participants, depending on the research design. Phenomenological studies typically need 5 to 25 participants. Grounded theory studies need 20 to 30. Case studies may focus on a single case. The guiding principle is data saturation: continue collecting data until new interviews or observations are no longer producing new themes. Justify your sample size in your methodology section based on your design and the concept of saturation.

What software should I use for qualitative data analysis?

NVivo, ATLAS.ti, and MAXQDA are the three most widely used qualitative data analysis software packages. All three help you organise, code, and retrieve data. They do not analyse your data automatically. The analytical thinking is yours. For smaller studies (under 15 interviews), manual coding with printed transcripts and highlighters is still a perfectly valid approach. Choose based on your budget, your institution’s licences, and your comfort level with technology.

How do I establish rigour in qualitative research?

Use Lincoln and Guba’s four criteria: credibility (through member checking, triangulation, and prolonged engagement), transferability (through thick description of context and participants), dependability (through a detailed audit trail of your research decisions), and confirmability (through reflexivity and grounding your findings in the data). Describe which of these strategies you used in your methodology section. Reviewers expect to see an explicit discussion of rigour in any qualitative paper.