Bibliographic record
Abstract
How do ideas evolve in the context of collaborative design? This research explores the framing strategies and tools involved in the co-construction of a shared understanding in the early stages of a design project. We observed a team of four industrial design students working to design a popup shop. We found that, while the key design elements of the solution were present from the early stages of discussion, they were continually framed and reframed through intense verbal discussion supported by sketching reflection-in-action (individual or collective) that help each team member make sense about the popup shop branding, user experience, visibility, structure, etc. The design ideas were crystallized at the end of the fourth working session. The research identifies patterns of framing, deframing and reframing of ideas that emerged from different symbolic elements associated with a brand, allowing students to design customized, non-standard, impressive and complex forms. Linking these patterns with specific ‘designerly actions’ led us to develop an empirically grounded model of the framing cycle. This model extends previous work of Schôn and Dorst and Valkenburg to specifically take into account collaborative design situations. In such situations, discussion among team members plays a vital role in clarifying, explaining, and interpreting as well as in encouraging reflection and critique.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".