RESEARCH AND TEACHING Collaborative Testing: Evidence of Learning in a Controlled In-Class Study of Undergraduate Students
Bibliographic record
Abstract
In collaborative two-stage exams, students complete a test as individuals and then immediately complete the same, or very similar, test in groups. We compared twostage collaborative testing with individual testing to determine which format has a greater effect on student learning in an undergraduate Earth and Ocean Science course. A crossover design allowed students to participate in both the control (individual) and treatment (collaborative) conditions. In both the individual and collaborative conditions, students completed the same set of questions twice, which controlled for any potential performance gain caused by more frequent testing. Learning was measured as the change in students ’ individual performance on questions given in the individual stage and after the midterm, calculated as percent change and normalized change. When students were tested in groups, they showed significantly greater improvement on subsequent individual testing then when tested only as individuals. There was no significant difference in the amount of improvement experienced by “upper, ” “middle, ” or “lower” achieving students as categorized by their first-stage midterm score. Most postsecondary institutions assess student learning with independent testing, that is, students complete the test on their own with no help from peers or outside resources. An alternative to this traditional format is the collaborative test, in which students work together in small groups to answer test questions. In the two-stage exam, perhaps the most common method of collaborative testing, students independently complete a test and then immediately complete the same, or similar, test again in groups of four; a proportion of each student’s grade is assigned to the independent- and group-test sections
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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 | 0.019 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".