A novel approach to needs assessment in curriculum development: Going beyond consensus methods
Bibliographic record
Abstract
BACKGROUND: Needs assessment should be the starting point for curriculum development. In medical education, expert opinion and consensus methods are commonly employed. AIM: This paper showcases a more practice-grounded needs assessment approach. METHODS: A mixed-methods approach, incorporating a national survey, practice audit, and expert consensus, was developed and piloted in thrombosis medicine; Phase 1: National survey of practicing consultants, Phase 2: Practice audit of consult service at a large academic centre and Phase 3: Focus group and modified Delphi techniques vetting Phase 1 and 2 findings. RESULTS: Phase 1 provided information on active curricula, training and practice patterns of consultants, and volume and variety of thrombosis consults. Phase 2's practice audit provided empirical data on the characteristics of thrombosis consults and their associated learning issues. Phase 3 generated consensus on a final curricular topic list and explored issues regarding curriculum delivery and accreditation. CONCLUSIONS: This approach offered a means of validating expert and consensus derived curricular content by incorporating a novel practice audit. By using this approach we were able to identify gaps in training programs and barriers to curriculum development. This approach to curriculum development can be applied to other postgraduate programs.
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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 | 0.006 | 0.008 |
| 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) | 0.001 | 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".