Comparison of the effectiveness of collaborative groups and peer instruction in a large introductory physics course for science majors
Bibliographic record
Abstract
We report on an experiment comparing examinations of concepts using slightly modified peer instruction (MPI) interventions with a conceptual conflict strategy based on collaborative groups (CG). Four interventions were utilized in two sections of an introductory physics course for science students. Both instructors and strategies were alternated in the two classes so that instructor dependence could be factored out and so that each class could serve as both an experimental and a control group. The gain on the Force Concept Inventory (FCI) used as a pre- and post-test is essentially the same in both classes. The instructors were experienced in use of MPI, but this was the first time that these instructors had used a collaborative group activity in their classes and only used it for the two interventions in each class described in this paper. CG appears to be more effective as a teaching method than PI. It also should be noted that the effectiveness of both teaching methods seems to be instructor independent as long as the instructors followed the same protocol.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".