Your study design is the plan for conducting your research. In qualitative research, the choice of design is shaped by your research methodology, which includes your ontological and epistemological position, theoretical framework, and broader research paradigm. These influence how you define your research problem, your role in the study, your approach to selecting participants and collecting data, and how you analyse and interpret your findings. Qualitative research aims to develop an in-depth understanding of people’s experiences, meanings, and social contexts, and therefore qualitative study designs are generally situated within interpretivist, constructivist, or critical paradigms.
This page outlines the key features of seven of the most commonly used qualitative study designs.
Case studies involve an in-depth exploration of a particular individual, group, event, or phenomenon within its real-life context using a variety of data sources. There are different types of case studies, for example intrinsic, instrumental, and collective. This type of study design is useful when you want to gain an in-depth understanding of one or a few cases, uncover rich details, and explore complex interactions that cannot be captured by surveys or experimental methods.
Seminal authors: Stake, Yin
Common data collection methods: multiple sources, including interviews, focus groups, observations and documents
Common data analysis techniques: aggregation; direct interpretation
Example thesis: Resilience and Women in the Maldives post-disaster: A case study
Grounded theory is a research design focused on generating or discovering theory that is grounded in systematically collected and analysed data. The theory emerges inductively from the data rather than being imposed in advance. There are two types of grounded theory: classic and constructivist. This type of study design is useful when you want to explore a process, action, or interaction for which no existing theory adequately explains what is happening.
Seminal authors: Glaser, Strauss, Corbin, Charmaz
Common data collection methods: interviews
Common data analysis techniques: open, axial, and selective coding; initial and focused coding
Phenomenology is a research approach focused on exploring and understanding the lived experiences of individuals. It can be descriptive (including transcendental phenomenology), which aims to detail those experiences, or interpretive (hermeneutical phenomenology), which also seeks to interpret their meaning. This type of study design is useful when you want to explore a phenomenon from the perspective of those who have experienced it.
Seminal authors: Husserl, Heidegger, Moustakas, van Manen
Common data collection methods: interviews
Common data analysis techniques: bracketing (epoché); clustering of meanings; theme identification; textural and structural descriptions; thematic analysis
Example thesis: Phenomenological understandings of higher education students with flow in the online learning environment
Ethnography is a research design that focuses on exploring and understanding the culture, behaviours, and social interactions of a group or community through immersive observation. This type of study design is useful when you are interested in group culture, norms, and practices, and in understanding how and why people behave in particular social settings.
Seminal authors: Malinowski, Geertz, Hammersley, Atkinson
Common data collection methods: observations, interviews, informal conversations, documents
Common data analysis techniques: thematic coding; constant comparison; narrative or discourse analysis; reflexive interpretation
Example thesis: Lala Land: A Discursive Ethnography of Professional Commercial Photographers
(Participatory) action research is a practitioner-centred research approach involving cycles of planning, action, observation, and reflection to solve problems and improve practices or systems in real time, often with participants as partners. This type of study design is useful when you want to engage participants in the research process to address practical problems and empower the people or groups involved.
Seminal authors: Lewin, Freire, Fals-Borda, Reason, Heron
Common data collection methods: interviews, focus groups, observations, surveys, and reflective journals, usually obtained iteratively
Common data analysis techniques: thematic analysis; reflective analysis; collaborative analysis, conducted iteratively to inform and evaluate action across research cycles
Example thesis: Srikandi: A participatory action research project with women from Indonesia to increase HIV testing
Qualitative description is a study design focused on straightforward, low-inference descriptions of participants’ experiences in their own words. This type of study design is useful when you need a clear, straightforward description of a phenomenon.
Seminal authors: Sandelowski
Common data collection methods: interviews, focus groups, and can also include observations and documents
Common data analysis techniques: qualitative content analysis
Discourse analysis is an approach focused on analysing language use to understand how social, cultural, and political meanings are constructed. This type of study design is useful when you want to examine how language constructs social realities, identities, power relations, or ideologies within a specific context.
Seminal authors: Foucault, Fairclough, van Dijk, Gee
Common data collection methods: texts and communication content, interviews
Common data analysis techniques: discourse analysis
Example thesis: Rethinking energy development to prioritise equity: The case of Cambodia
If you would like to consolidate your understanding of the qualitative study designs outlined above, you may find the following activity helpful: