Gastroenterology Fellowship Training: Approaches to Curriculum Assessment and Evaluation
Bibliographic record
Abstract
BACKGROUND: Medical education requires ongoing curriculum development and evaluation to incorporate new knowledge and competencies. The Kern model of curricular development is a generic model to guide curriculum design, whereas the Royal College of Physicians and Surgeons of Canada (RCPSC) has a specific model for curriculum development through its accreditation structure. OBJECTIVE: To apply the Kern model to an assessment of a residency program in gastroenterology. METHODS: A case study was used, which is a method of qualitative research designed to help researchers understand people and the societal contexts in which they live. RESULTS: The six steps involved in the Kern model of curricular development include problem identification; needs assessment; establishing objectives; establishing educational strategies; implementation; and evaluation. The steps of the RCPSC model of curriculum development include establishing an administrative structure for the program; objectives; structure and organization of the program; resources; clinical, academic and scholarly content of the program; and evaluation. Two differences between the models for curriculum development include the ability of the Kern model to conduct problem identification and learner needs assessment. Identifying problems that exist suggests a need for an educational program, such as the long wait times for gastroenterology referrals. Assessing learner needs allows for the development of a tailored curriculum for the trainee. CONCLUSIONS: The Kern model and RCPSC model for curriculum development are complementary. Consideration by the RCPSC should be provided to add the missing elements of curriculum design to the accreditation structure for completeness.
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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 | 0.302 | 0.331 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".