Influence of a School-Based Cooking Course on Students’ Food Preferences, Cooking Skills, and Confidence
Bibliographic record
Abstract
A quasi-experimental study was conducted to evaluate the influence of Project CHEF, a hands-on cooking and tasting program offered in Vancouver public schools, on students' food preferences, cooking skills, and confidence. Grade 4 and 5 students in an intervention group (n = 68) and a comparison group (n = 32) completed a survey at baseline and 2 to 3 weeks later. Students who participated in Project CHEF reported an increased familiarity and preference for the foods introduced through the program. This was statistically significant (P ≤ 0.05) for broccoli, swiss chard, carrots, and quinoa. A higher percentage of students exposed to Project CHEF reported a statistically significant increase (P ≤ 0.05) in: cutting vegetables and fruit (97% vs 81%), measuring ingredients (67% vs 44%), using a knife (94% vs 82%), and making a balanced meal on their own (69% vs 34%). They also reported a statistically significant increase (P ≤ 0.05) in confidence making the recipes introduced in the program: fruit salad (85% vs 81%), minestrone soup (25% vs 10%), and vegetable tofu stir fry (39% vs 26%). Involving students in hands-on cooking and tasting programs can increase their preferences for unpopular or unfamiliar foods and provide them with the skills and cooking confidence they need to prepare balanced meals.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".