The role of assessment in competency-based medical education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Competency-based medical education (CBME), by definition, necessitates a robust and multifaceted assessment system. Assessment and the judgments or evaluations that arise from it are important at the level of the trainee, the program, and the public. When designing an assessment system for CBME, medical education leaders must attend to the context of the multiple settings where clinical training occurs. CBME further requires assessment processes that are more continuous and frequent, criterion-based, developmental, work-based where possible, use assessment methods and tools that meet minimum requirements for quality, use both quantitative and qualitative measures and methods, and involve the wisdom of group process in making judgments about trainee progress. Like all changes in medical education, CBME is a work in progress. Given the importance of assessment and evaluation for CBME, the medical education community will need more collaborative research to address several major challenges in assessment, including "best practices" in the context of systems and institutional culture and how to best to train faculty to be better evaluators. Finally, we must remember that expertise, not competence, is the ultimate goal. CBME does not end with graduation from a training program, but should represent a career that includes ongoing assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it