Authorised cheat sheets in undergraduate biology: Using pictographic organisers to foster student creative cognition
Bibliographic record
Abstract
Abstract Science student development of creative thinking ability is not sufficiently promoted and can even be inadvertently discouraged by current methods of instruction. Aimed at addressing this issue, the present study examined an undergraduate biology course in which scientific content instruction and creative drawing were integrated through use of authorised cheat sheets (personalised visual aids that students draw to bring for consultation during course examinations). Through a mixed‐method analysis, we sought to identify the forms of student cognition that resulted, and how effective this pedagogical strategy was in promoting student creativity. Results indicate predominance of intermediary levels of student creative performance centred on the alteration of ideas and images encountered during the course (83% of drawings). In contrast, creation of original and novel images was considerably less frequent (only 6% of drawings). Authorised cheat sheets were found to be effective as a pedagogical tool for promoting student creativity in the form of structured imagination. Rather than limitless and unconstrained, the resulting student creativity was structured (constrained) by existing conceptual knowledge. Illuminating the relationship between pedagogical tools in a science classroom and students' emergent creativity, the present study underscores the critical need for educators to support student development as future creative professionals.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".