Applying a reflexive framework to evaluate a communication skills curriculum
Bibliographic record
Abstract
After creating and delivering an educational curriculum, medical educators must ultimately evaluate the effectiveness of the implemented curriculum. Seasoned educators can benefit from using an established framework to help them structure a thorough, complete curricular evaluation; however, novice educators may have difficulty in transforming the concept of evaluation into a concrete process. The RUFDATA (Reasons and purpose, Uses, Focus, Data and evidence, Audience, Timing, and Agency) framework is one such paradigm. It is a well-recognized tool consisting of a reflexive framework that can guide medical educators to evaluate their own medical education curriculum. Just as important, it enables medical educators to reflect on the reasons behind the evaluation. This insight, in turn, can foster a spirit of evaluation, thus helping to ingrain it into the local educational culture. By using the evaluation of our communication skills curriculum as an example, this article describes how educators can apply the RUFDATA framework to evaluate their own curriculum.
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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 | 0.003 | 0.110 |
| 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 | 0.001 |
| 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".