Student Performance on an Objective Structured Clinical Exam Delivered Both Virtually and In-Person
Bibliographic record
Abstract
OBJECTIVE: Passing a milestone objective structured clinical examination (OSCE) is a graduation requirement for the University of Waterloo Pharmacy students. In January 2021, the milestone OSCE was offered concurrently both virtually and in-person, with students being able to choose their desired format. The purpose of this study was to compare student performance between the 2 formats and to identify factors that may have predicted student choice of format. METHODS: analysis. Prior academic performance variables were analyzed to identify predictors of the chosen exam format. Student and exam personnel surveys were used to capture OSCE feedback. RESULTS: A total of 67 students (56%) participated in the in-person OSCE, and 52 students (44%) participated virtually. There were no significant differences in overall exam averages or pass rates between the 2 groups. However, virtual exam-takers scored lower in 2 of 7 cases. Previous academic performance did not predict the choice of exam format. Feedback surveys indicated that the exam organization was perceived as a strength regardless of format, but in-person students felt more prepared for the exam than virtual exam-takers with technical challenges and difficulty navigating station resources being noted as barriers in the virtual offering. CONCLUSION: Virtual and in-person administration of a milestone OSCE resulted in similar student performance, with slightly lower performance on 2 individual case scores with virtual delivery. These results may inform the future development of virtual OSCEs.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".