Modelling and Fostering Creativity: Two Post- Secondary EAL Teachers’ Journey
Bibliographic record
Abstract
Scholarly literature is replete with suggestions for fostering creativity in both teachers and students; however, few articles exist where practitioners appraise these methods and generate theories of their own.After a semester of team teaching using a creative project-based learning (PBL) approach, we reviewed, through a mutual interview process, the theory that underpinned and resulted from our experiences in our English language learning (ELL) classrooms.Our experience with this approach confirmed previous findings on creative teaching, but also included unanticipated challenges and benefits, such as a greater need for feedback and an increased sense of empowerment and ownership in our students.Copie de diffusion et de conservation autorisée par la licence CC-BY-NC-ND Diffusé par le Centre de documentation collégiale dans EDUQ.info 26 p.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.012 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| 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".