Development and use of a computerized system to track the competency development of family medicine residents: analysis of the convergence between system proposals and assessor decisions
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
Abstract In recent decades, a number of training environments have moved toward program approaches targeting the development of competencies. Because of their complexity, monitoring the development of those competencies is a considerable challenge. Our hypothesis is that a computerized system could help overcome this challenge if it is well accepted by its users. We first summarize the context surrounding the implementation of such approaches. Next, we present a computerized assessment system established in the Family Medicine Residency Program of Laval University (Québec, Canada) that we have developed for tracking the development of residents’ competencies. We then present the analysis of interactions between the system and users and the various proposals that were made to improve the system and longitudinal tracking of the development of the targeted competencies. We consider that this research provides useful guidelines for the computerized monitoring of learners' competencies development and for the design of such systems.
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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it