Recipes for Success: Experiential Pathways to Meaningful Learning in the Humanities Classroom
Bibliographic record
Abstract
Today's students have a high appetite for experiential learning, but for a variety of reasons have been conditioned to look outside of the humanities for such opportunities.Challenging the recurring student narrative that humanities disciplines have little relevance to everyday life and do not lead to profitable or meaningful careers, Cucina italiana: Italian History and Culture through Food is an innovative, experience-driven undergraduate course whose enrolments are on the rise at the University of Toronto Mississauga.Utilizing collaborative learning activities and study abroad experiences that give students the opportunity to smell, taste, and touch the food products that they learn about in class, Cucina italiana demonstrates how an instructor's commitment to fostering High-Impact Practices and integrating cocurricular or extra-curricular opportunities into coursework can energize students in Italian Studies-and, more broadly, humanities disciplines-enabling higher levels of student engagement and more meaningful learning experiences.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".