Feasibility of self-directed learning in clerkships
Bibliographic record
Abstract
BACKGROUND: Self-directed learning has been well described in preclinical settings. However, studies report conflicting results when self-directed initiatives are implemented in clinical clerkships. AIM: To explore the feasibility of self-directed learning stimulated by clinical encounter-cards (CECs) in clinical clerkships. METHODS: Two focus groups of year-four and year-five students were interviewed about the usefulness of CECs to their learning in clerkships. The CECs were then introduced in two cohorts of 248 year-four and 250 year-five medical students and evaluated on a nine-point scale with regard to usefulness and feasibility. RESULTS: The pilot groups reported that the CECs had positive effects in terms of engaging in diagnostic reasoning, reflection on management plans, and professional identity formation. However, the two large cohorts of students rated the usefulness of the CECs on learning in clerkship low (year-four: mean 2.92, SD 1.54; year-five: mean 2.28, SD 1.06) along with preceptor support (year-four: mean 2.68, SD 1.62; year-five: mean 2.59, SD 1.78, p = 0.34). CONCLUSION: Self-directed CECs can have a positive effect on participation and clinical reasoning but are highly dependent on the context of use. Self-directed learning initiatives that aim to increase participation in communities of practice may not be feasible without major faculty development initiatives.
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How this classification was reachedexpand
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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 teacher head, 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".