Improving the Effectiveness of Students in Groups With a Centralized Peer Evaluation System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We describe the impact of a centralized electronic peer evaluation system on the group effectiveness of undergraduate business students over a pair of semesters. Using a quasi-experimental design, 389 undergraduate students evaluated, and were evaluated by, their peers using a web-based system that captures peer evaluations in quantitative and qualitative formats and allows for the reception of anonymous feedback. Results show that the effectiveness of students, as perceived by their peers, increased over semesters. This effect could be directly linked to the use of the system. The results of this study underscore the benefit of centralizing peer evaluations for the assessment of important skills and their development in higher education. The implication of these results and possible avenues of research are detailed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it