Involving users in the refinement of the competency-based achievement system: An innovative approach to competency-based assessment
Bibliographic record
Abstract
BACKGROUND: Competency-based assessment innovations are being implemented to address concerns about the effectiveness of traditional approaches to medical training and the assessment of competence. AIM: Integrating intended users' perspectives during the piloting and refinement process of an innovation is necessary to ensure the innovation meets users' needs. Failure to do so results in no opportunity for users to influence the innovation, nor for developers to assess why an innovation works or does not work in different contexts. METHODS: A qualitative participatory action research approach was used. Sixteen first-year residents participated in three focus groups and two interviews during piloting. Verbatim transcripts were analyzed individually and then across all transcripts using a constant comparison approach. RESULTS: The analysis revealed three key characteristics related to the impact on the residents' acceptance of the innovation as being a worthwhile investment of time and effort: access to frequent, timely, and specific feedback from preceptors. Findings were used to refine the innovation further. CONCLUSION: This study highlights the necessary conditions for assessing the success of implementation of educational innovations. Reciprocal communication between users and developers is vital. This reflects the approaches recommended in the Ottawa Consensus Statement on research in assessment published in Medical Teacher in March 2011.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".