A follow-up to the Mission to Mars post, which describes the experimental work. This one is about the methodology layer underneath it — specifically, what I got wrong.
The Mistake Was a Category Error
My background is in physics. I entered physics education research through the astro-lab and chose a framework that felt close to the work: empathise, define, ideate, prototype, test. I was building and revising classroom experiments. The design-thinking vocabulary described that activity neatly.
It did not specify how observations became defensible research claims. I had a design workflow and treated it as though it supplied sampling, data collection, analysis, reflexivity, and standards of inference. Colleagues advised me to use grounded theory because the material I most needed to understand was in student responses, including responses the design did not anticipate.
For my thesis, they were right.
That sentence needs a boundary. Design thinking is a family of innovation and design practices. Design-based research (DBR) is an educational research tradition that deliberately joins theory, intervention design, empirical study, and revision in authentic settings. They overlap, but they are not synonyms. The earlier version of this essay criticised the first and repeatedly assigned the criticism to the second.
What Design-Based Research Can Do
The Design-Based Research Collective describes DBR as intertwining the design of learning environments with theoretical claims about teaching and learning. Its cycles are not simply “try it and make it better.” A rigorous study can document the conjecture embodied in a design, collect systematic evidence, explain revisions, test consequences, and produce context-sensitive design principles or theory.
That can be a doctoral contribution. It need not pretend that an intervention has a context-free effect, and it need not reduce to a practitioner manual. Transferability comes from specifying mechanism, context, and design principle, not from erasing the setting.
DBR can also fail. A researcher who designed the intervention may privilege expected outcomes, revise several things at once, use an instrument aligned too tightly with the design, or leave the analytical chain implicit. Those are risks to manage through study design, triangulation, negative cases, documentation, and appropriate analysis. They are not proof that DBR has “no systematic answer.”
My work had too much of the workflow and too little of that chain.
What Grounded-Theory Techniques Offered
Grounded theory is not one unchanging recipe. Glaser and Strauss’s original programme, Strauss and Corbin’s later procedures, and constructivist variants disagree about coding, prior literature, researcher position, and what it means for theory to be “grounded.” Shared techniques include constant comparison, memo writing, category development, and theoretical sampling directed by the emerging analysis.
Theoretical sampling does not mean walking into the field with no question and no practical boundary. It means that analytical needs influence which data are sought next. Saturation is likewise a methodological judgment about category development, not an automatic counter that announces when a sample is complete.
Those techniques suited the weakness in my project. They would have forced me to record how I coded a response, compare it with disconfirming cases, write down why a category changed, and show how the next observation followed from the analysis. Grounded theory would not automatically remove bias or validate the intervention. It would make a different kind of claim possible: a theory built through a traceable comparison of student accounts.
The Observation I Let Pass
In the Mission to Mars activity, a push-fit lid sometimes came off under a pressure difference. I expected the event to clarify the direction of the net force. Students did not all interpret it that way. Some described internal air pushing outward. Some retained the language of an external vacuum pulling. Some remained unsure.
I noted this, but I did not build a systematic corpus, coding procedure, or theoretical sample around it. The observation is therefore an anecdote about my implementation, not evidence for a transferable typology of pressure reasoning.
That is the missed opportunity. A grounded-theory-informed study might have developed such a typology; it might instead have shown that my categories were wrong or that the data were too thin. The counterfactual cannot be promoted to a result.
The design did not force me to discard the unexpected response as noise. My framing and analysis practice made it easy to do so.
The Postmortem
The choice was never “make an artefact or produce theory.” DBR can do both. Grounded theory can analyse a phenomenon without evaluating whether an intervention caused improvement. Other questions might require case study, interaction analysis, thematic analysis, experiment, or mixed methods. The research question and claim should govern the methodology, not the comfort of the researcher or the prestige of a label.
What I needed was an explicit chain:
- What claim am I trying to make?
- What data could support or contradict it?
- How will those data be sampled, analysed, and compared?
- What role did I play in producing both intervention and interpretation?
- Which part is local observation, design principle, theoretical proposal, or measured effect?
I chose a useful way to design and mistook it for a complete answer to those questions. A more rigorous DBR design might have answered them. Grounded-theory techniques might have changed the question toward the unexpected student responses. In the thesis I was actually writing, the latter was the correction people were trying to give me.
I would have understood more if I had taken it earlier.
The experimental work is described in Mission to Mars. For a later use of qualitative methodology in a related context, see AI Transcription and Grounded Theory.
Methodology literature checked through 2026-07-11.
References
Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine.
Strauss, A., & Corbin, J. (1998). Basics of Qualitative Research (2nd ed.). SAGE.
The Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5–8. https://doi.org/10.3102/0013189X032001005
Barab, S., & Squire, K. (2004). Design-based research: Putting a stake in the ground. The Journal of the Learning Sciences, 13(1), 1–14. https://doi.org/10.1207/S15327809JLS1301_1
Changelog
- 2026-07-11: Separated design thinking from design-based research, removed universal claims that DBR cannot be systematic or doctoral, bounded grounded-theory sampling and saturation, and recast the missed student-response analysis as a counterfactual rather than a result.