From Spherical Cows to Schrödinger’s Cat: what students want to learn in physics
Bibliographic record
Abstract
Abstract This paper reflects on feedback received from 161 Ontario grade 12 physics students between 2017–2018 and 2020–2023, on the content and delivery in different modes (face-to-face, online, hybrid) of the 2008 Ontario Grade 12 Physics—University Preparation course (SPH4U). Across modes, students considered Revolutions in Modern Physics significantly more interesting and less stressful than any of the other four units. Students also identified Dynamics as significantly less interesting than all of the units, and found it significantly more stressful than all units other than Fields. Students were most interested in topics not previously studied (e.g. Special Theory of Relativity) that they felt promoted new ways of thinking. Adjusting to grade 12 expectations combined with more challenging course concepts were the primary contributors of stress. Included is a discussion of physics education reform, and the role of physics education in science, technology, engineering and mathematics.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".