What Is Qualitative Research?

Qualitative research is a research approach that seeks to understand human experience, meaning-making, and social context through language and description rather than reducing them to numerical values. Data consist of materials that capture participants’ worlds from the inside, including observations, interviews, documents, and video recordings. Analysis proceeds inductively, allowing patterns and concepts to emerge from the data¹.

Its epistemological foundations lie in interpretivism and constructivism. Guba and Lincoln characterized the ontology of the constructivist paradigm as relativism (realities are multiple and constructed) and its epistemology as subjectivism (findings are created through interaction between investigator and respondents)². Under this view, reality does not exist independently of the observer but is constituted through people’s interpretations and social interactions. The researcher is also a participant in meaning construction; rather than eliminating the researcher’s interpretive role, this stance calls for reflexive positioning.

The validity of qualitative research is evaluated not through statistical significance but through four criteria: credibility, transferability, dependability, and confirmability². These criteria correspond respectively to internal validity, external validity, reliability, and objectivity in quantitative research, but they have been redefined in accordance with constructivist epistemology.

What Is Quantitative Research?

Quantitative research is a research approach that measures relationships among variables through numerical data and tests them using statistical methods. Hypotheses are formulated in advance, and the research follows a deductive logic in which data either support or refute those hypotheses¹.

Its epistemological foundations lie in positivism and postpositivism. Positivism assumes that an objective reality exists independently of the observer and that laws can be discovered through appropriate measurement. Postpositivism modifies this assumption, holding that while complete objectivity is unattainable, reality can be approximated through the critical scrutiny of the research community². Creswell and Creswell characterize this stance as one that “examines problems based on a deterministic philosophy in which causes determine effects”¹.

The validity of quantitative research is evaluated through internal validity, external validity, reliability, and objectivity. Reproducibility is expected: ideally, another researcher following the same procedures should obtain similar results.

Key Differences

The differences between qualitative and quantitative research are not merely differences in specific techniques; they trace back to the epistemological level of how reality is apprehended. The following five dimensions provide a framework for comparison.

• Epistemology: Quantitative research presupposes an objective reality independent of the researcher and seeks to discover the laws governing that reality (positivism, postpositivism). Qualitative research regards reality as a product of people’s interpretations and interactions and aims to describe its structures of meaning (interpretivism, constructivism)².
• Data: Quantitative research deals with numerical data and establishes operational definitions of measurement in advance. Qualitative research deals with non-numerical data such as text, images, audio, and observational records, and the scope of data may evolve as the research progresses¹.
• Analysis: Quantitative research tests hypotheses through statistical inference. Qualitative research constructs concepts through inductive methods such as coding, category generation, and thematic interpretation³.
• Generalizability: Quantitative research aims for statistical generalization to a population. Qualitative research provides thick description of a particular context, enabling readers to judge whether findings can be transferred to their own contexts (transferability)².
• Validity criteria: Quantitative research is evaluated through internal validity, external validity, reliability, and objectivity. Qualitative research is evaluated through credibility, transferability, dependability, and confirmability². In the context of architectural research, Groat and Wang point out that these differing criteria shape the choice of research design itself⁴.

Strengths and Limitations of Qualitative Research

The strength of qualitative research lies in its capacity to capture the structure of phenomena that cannot be reduced to numbers. It can describe why participants acted as they did and in what context a particular judgment arose, using the actors’ own words and logic. Leavy notes that qualitative research is suited to “exploratory questions, the discovery of new concepts, and understanding from the participant’s perspective”³. It is most effective in early-stage research that opens up unknown territory or in situations requiring deep understanding of a small number of cases.

At the same time, it has limitations. Sample sizes are small, and statistical generalization is not possible. Data collection and analysis are time-intensive, and the researcher’s biases can readily influence results. Because analytical procedures vary from one researcher to another, external verification of reproducibility can be difficult. Ensuring validity requires combining multiple procedures, including member checking, triangulation, and thick description¹.

Strengths and Limitations of Quantitative Research

The strength of quantitative research lies in its ability to derive statistically generalizable findings from large samples. Hypothesis testing follows explicit procedures, yielding high reproducibility and facilitating comparison of results. Mechanisms for controlling bias are well established, including randomization, blinding, and the use of control groups¹.

At the same time, it has limitations. Because variables to be measured must be determined in advance, it is difficult to capture unanticipated phenomena. What can be grasped numerically is limited to particular aspects of a phenomenon; actors’ motivations, contexts, and meaning-making fall outside the scope of measurement. As Creswell and Creswell observe, there is a tendency for “the voices of participants and the reflexivity of the researcher about their own biases to recede into the background”¹. Because operational definitions delimit the object of study, there is an attendant risk of oversimplifying phenomena.

Methodological Choice in Design Research

Design is an exploratory intellectual activity that envisions and realizes what does not yet exist. Simon defined design as “courses of action aimed at changing existing situations into preferred ones” and positioned it as a “science of the artificial,” distinct from the analytical natural sciences⁵. Schon characterized designers’ thinking as “reflection-in-action,” describing a process in which problems and solutions are co-constructed through dialogue with the situation⁶. Cross termed this mode of knowing “designerly ways of knowing” and characterized it as a third culture of knowledge, distinct from both scientific and humanistic methods⁷.

Because of this exploratory character, qualitative methods play a major role in design research.

Qualitative methods are well suited to research that seeks to understand the design process itself. Protocol analysis is a method for reconstructing designers’ thought processes from verbal data; it is one of the methods Cross used to empirically elucidate “designerly ways of knowing”⁷. Ethnography involves entering users’ lifeworlds and describing the contexts and meanings of behavior through participant observation and interviews. It is used in the early stages of design to explore users’ latent needs and practices. Case studies track the unfolding of a specific design project and analyze under what circumstances and why particular design decisions were made. Groat and Wang position the case study as a central method in architectural research, recognizing its role in bridging theory and practice⁴. Grounded theory is a method for building theory inductively from data and is employed when tackling phenomena that existing theories cannot explain.

Research through design is an approach that positions the practice of design itself as a research method. Zimmerman, Forlizzi, and Evenson argued that design artifacts embody research knowledge, proposing a methodology for “research through design” in HCI⁸. Stappers contended that designing itself is part of inquiry, with research questions being refined through the process of prototyping⁹. Fallman organized design research as a triangle of “design practice,” “design studies,” and “design exploration,” framing design research as a dynamic process in which these activities continuously transition into one another¹⁰¹¹. Although research through design does not fit entirely within the framework of qualitative research, its exploratory character and its generation of knowledge through artifacts give it a strong affinity with qualitative epistemology.

On the other hand, quantitative methods are needed at the stage of evaluating design outcomes. Usability testing measures the ease of use of an interface through objective metrics such as task completion rates and error rates. Survey research uses standardized scales such as the SUS (System Usability Scale) to quantify subjective evaluations and make them comparable. Experiments (including A/B testing) manipulate design variables and verify their effects through comparison with control conditions. Eye tracking measures gaze movements to quantitatively assess the allocation of users’ attention.

The criterion for choosing a method in design research is the nature of the research question. If the question asks “what is happening?” or “why does this occur?,” qualitative methods are appropriate; if it asks “to what extent?” or “which is better?,” quantitative methods are appropriate¹. At the exploratory stage of design, the problem space itself is not yet defined, making it difficult to operationally define variables in advance. At this stage, describing phenomena and constructing concepts through qualitative methods takes priority. At the evaluative stage, when candidate solutions have been concretized, quantitative methods are called upon to objectively verify their effects (the academic mainstream status and limitations of this framing are examined in design-research-methodology-mainstream).

Mixed Methods Research

Mixed methods research is an approach that intentionally combines qualitative and quantitative methods within a single study. Creswell and Creswell define mixed methods research as a research design that “collects both qualitative and quantitative data and integrates the two for interpretation”¹. Its underlying epistemology is pragmatism, which takes “what works” as its criterion and adopts a flexible stance in selecting the methods best suited to the research question¹.

In design research, mixed methods can be particularly effective. A typical example is a sequential design in which ethnography discovers patterns of user behavior (qualitative phase), and the hypotheses derived from those findings are then tested through surveys or A/B testing (quantitative phase). Conversely, trends identified through statistical analysis of large-scale surveys can be deeply interpreted through a small number of interviews.

In their discussion of research methods for architecture, Groat and Wang note the utility of combining multiple research strategies while emphasizing that such combinations must be epistemologically coherent⁴. Simply using qualitative and quantitative methods side by side does not constitute mixed methods research. The research design must explicitly plan at what stage and how findings from the two methods will be integrated¹.

Given the exploratory character of design, mixed methods research is a well-suited methodological option for design research. The qualitative discoveries of the exploratory stage and the quantitative verification of the evaluative stage are, in the design process, inherently continuous. Mixed methods research provides a framework that methodologically secures this continuity within a single study.

References

Footnotes

1. Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). Sage. ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶ ↩⁷ ↩⁸ ↩⁹ ↩¹⁰ ↩¹¹

2. Guba, E. G., & Lincoln, Y. S. (1994). Competing paradigms in qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of Qualitative Research (pp. 105–117). Sage. ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶

3. Leavy, P. (2017). Research Design: Quantitative, Qualitative, Mixed Methods, Arts-Based, and Community-Based Participatory Research Approaches. Guilford Press. ↩ ↩²

4. Groat, L. N., & Wang, D. (2013). Architectural Research Methods (2nd ed.). Wiley. ↩ ↩² ↩³

5. Simon, H. A. (1996). The Sciences of the Artificial (3rd ed.). MIT Press. (Original work published 1969) ↩

6. Schön, D. A. (1983). The Reflective Practitioner: How Professionals Think in Action. Basic Books. ↩

7. Cross, N. (2006). Designerly Ways of Knowing. Springer. https://doi.org/10.1007/1-84628-301-9 ↩ ↩²

8. Zimmerman, J., Forlizzi, J., & Evenson, S. (2007). Research through design as a method for interaction design research in HCI. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ‘07), 493–502. https://doi.org/10.1145/1240624.1240704 ↩

9. Stappers, P. J. (2007). Doing design as a part of doing research. In R. Michel (Ed.), Design Research Now: Essays and Selected Projects (pp. 81–91). Birkhäuser. https://doi.org/10.1007/978-3-7643-8472-2_6 ↩

10. Fallman, D. (2003). Design-oriented Human-Computer Interaction. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ‘03), 225–232. https://doi.org/10.1145/642611.642652 ↩

11. Fallman, D. (2008). The Interaction Design Research Triangle of Design Practice, Design Studies, and Design Exploration. Design Issues, 24(3), 4–18. https://doi.org/10.1162/desi.2008.24.3.4 ↩