Use of Examination Wrappers to Direct Student Self-Assessment of Examination Preparation: A Pilot Study
Bibliographic record
Abstract
Metacognition is the act of thinking about one's own thought processes. There are long-term gains in learning among students who are trained to understand how the brain works and how they can control their own learning. Wrappers are short questionnaires provided at or near the time of completion of a lecture, assignment, or assessment to coach the student in thinking through the steps of metacognition (planning, monitoring, and adapting). As students completed the second and third of four examinations in a first-year veterinary anatomy course, they were invited to fill out an examination wrapper that asked them questions about examination preparation, where they felt they had had the most trouble with the examination, and what they might do differently before the next examination. Neither percentage change in scores from the second to the third and from the third to the fourth lecture or laboratory examination nor final grade for the course varied between the group of students who completed an examination wrapper and the group that did not. Students did not appear to change their behavior from one examination to the next. This was most likely because students lacked formal training in metacognition and therefore did not understand the value of completing the examination wrapper or the potential benefits of using their reflections. Future work will describe outcomes when learning objectives specific to metacognition are included in coursework in the veterinary curriculum.
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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 | 0.012 | 0.025 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".