‘Wait, wait, Dan, your turn’: Authority and Assessment in the Design Critique
Bibliographic record
Abstract
This paper explores assessment in graduate-level industrial design education. In particular, it considers how the assessment of students' design work is delivered and who delivers it. Through using conversation analysis to look in close-up detail at a number of short segments of tutor-student interaction, we consider how a tutor performs assessment himself and also coaches other students to assess, in ways that may significantly contribute to students' understanding of what assessment is and how it is to occur. We find that, although the data was not collected with attention to the gender of the participants, the way in which the participants perform the reviews does indicate that participant gender had some impact upon the interaction. Creating opportunities for students and instructors to reflect upon evaluation, and how it is performed, may better equip participants in design education to recognize, debate, and also change some of the discourses in which design practice is embedded and performed.
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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 | 0.055 | 0.163 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".