The academic half-day redesigned: A learner centered and systems-based curriculum
Bibliographic record
Abstract
Teaching curriculum, learner centered, CanMEDS Roles McGill University’s Pediatrics residency program revamped its academic half-day, in response to concerns from the residents and Curriculum Committee. These concerns included an overemphasis on subspecialty content, exclusive use of didactic lectures and opportunistic topics based on the interests of the “volunteer” instructors. The “new” curriculum places a greater emphasis on active learning with the explicit goal to ensure all residents achieve the competencies of a general pediatrician. Novel instructional methods include the incorporation of monthly simulation sessions to teach CanMEDS competencies and increased involvement of residents as teachers in case discussions and practical case sessions (electrocardiogram and chest x-ray interpretations). The curriculum is organized as a monthly systems-based schedule (e.g., Cardiology). Division directors are provided with the Royal College–based objectives for their service to cover during their respective 4-week teaching block and are asked to identify the instructors and create the teaching material. General pediatricians are involved as instructors whenever the topic allows, even when content is of a subspecialty nature. Instructors are offered suggestions on how to improve their use of interactive techniques. Residents are encouraged to engage in concurrent self-study to consolidate learning in the academic half-day and formative question sessions are used to assess learning and knowledge gaps. Preliminary feedback suggests that changes to the curriculum are viewed positively by residents and staff. A formal survey to evaluate the impact of the new curriculum is planned for the end of the academic year. We propose that our comprehensive, systems-based interactive format is practical and easy to implement, while allowing a more learner-centered educational experience.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".