Implementation and Student Assessment of a Two-stage Midterm Exam in a First-year Physical Chemistry Course for International Engineering Students
Bibliographic record
Abstract
Group exams have been shown to improve student performance, retention of material, and teamwork and communication skills. This paper assesses the opinion of students regarding group exams, and their perception of potential benefits and impacts on their learning, before and after having participated in one. Both a traditional and two-stage exam were performed in first-year physical chemistry courses in the engineering stream of Vantage College at UBC, which means the participating cohort is entirely composed of international students with a range of English-language communication skills.The overall experience of students with group exams, based on survey responses, was positive, and the large majority of students indicated they would like to continue using this format of exam in the future. The perception of group exams improved before and after having written one, with the students initially overestimating the difficulty, stress, and level of conflict associated with this process. Some students indicated less confidence that peer learning helped them improve their performance after having written the exam, but further study to elucidate the significance and the causes of this result.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".