From theory to practice: a roadmap for applying dual-process theory in design cognition research
Bibliographic record
Abstract
Dual-process theory categorises cognition into two types of processing: Type 1 which is intuitive, autonomous processing, and Type 2 which is reflective processing that burdens limited executive cognitive resources (i.e.working memory).A recent call for increased theory-driven research in the field of design has led to a framing of dual-process theory as a foundation for design research.This research note presents a roadmap for future dual-process theorydriven design research outlining three main stages: defining dualprocess theory constructs, determining research focus, and selecting research methods.Across these stages, we offer a conceptualisation of dual-process theory for design researchers, outlining the main concepts of the theory.We then present how a research study design must consider the nature of design problems (complex, illstructured, ambiguous), designers, and the practice of design.Finally, we outline the main methods employed in dual-process theory research: behavioural, physiological, and self-report measures, suggesting ways to adapt such methods to design contexts.Ultimately, this work presents how dual-process theory may connect with theories of cognition often considered in design and offers a path forward for dual-process theory-driven design research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.123 | 0.121 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.016 | 0.010 |
| Science and technology studies | 0.006 | 0.046 |
| Scholarly communication | 0.028 | 0.044 |
| Open science | 0.010 | 0.016 |
| Research integrity | 0.013 | 0.021 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".