Shifts in Students Attitudes toward an Integrated Math and Physics Curriculum
Bibliographic record
Abstract
In September of 2012, the University of Guelph launched a new first year introductory math and physics course. The Integrated Physical Science (IPS) course was designed to replace the traditional first year calculus and physics courses. The intent was that combining these courses would allow learning across these two disciplines to be mutually supportive. The content typical of first-year physical and mathematical sciences is fully retained with the math enhanced in support of some physics topics. The integration of schedules allows for a just-in-time approach to the provision of necessary mathematical tools needed to solve problems in physics, while simultaneously providing context to the mathematical concepts. An attitudinal survey was conducted on two cohorts of students who have been through the IPS course and one cohort of students who went through a standard program of separate first year math and physics courses. The two IPS cohorts were compared to the non-IPS students to inquire as to whether groups had a significant difference in attitudes along several categories. The preliminary results show indications that IPS students have a more positive and sophisticated attitude towards their first year undergraduate experience. This initiative is an exciting opportunity to enhance first-year science education and growth within our existing programs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".