Introducing and evaluating competency‐based teaching in Rwandan teaching hospitals ő a student vs. teacher perspective (535.5)
Bibliographic record
Abstract
This study aims to determine if competency‐based teaching improves the effectiveness of surgeons and residents as teachers, and enhances the student learning experience (LE). Twenty Obstetric surgeons and residents were surveyed to evaluate their perceived effectiveness as teachers. Forty senior clerks were surveyed to gain a student view of the teachers' effectiveness. Teachers then attended seminars based on the CANmeds Communicator and Professional roles, and were surveyed to determine the applicability to teaching. Students were re‐surveyed to determine if the new teaching styles enhanced their LE. Learning objectives (LO) was a new concept to 94% of teachers. After the Communicator seminar, 100% believed that using LO would improve student‐teacher communication. 75% of students confirmed this belief and 71% reported a better LE. Only 36% of teachers had prior Professionalism teaching training. Post‐seminar, 89% and 84% increased their knowledge of, and attitudes toward, teaching this role, respectively. This study suggests that competency‐based teaching can improve teacher effectiveness and may enhance the student LE. This study has expanded to other departments for interdepartmental comparisons.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".