A Comparison of Resident-Completed and Preceptor-Completed Formative Workplace-Based Assessments in a Competency-Based Medical Education Program
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In competency-based medical education (CBME), should resident self-assessments be included in the array of evidence upon which summative progress decisions are made? We examined the congruence between self-assessments and preceptor assessments of residents using assessment data collected in a 2-year Canadian family medicine residency program that uses programmatic assessment as part of their approach to CBME. METHODS: This was a retrospective observational cohort study using a learning analytics approach. The data source was archived formative workplace-based assessment forms (fieldnotes) stored in an online portfolio by family medicine residents and preceptors. Data came from three academic teaching sites over 3 academic years (2015-2016, 2016-2017, 2017-2018), and were analyzed in aggregate using nonparametric tests to evaluate differences in progress levels selected both within and between groups. RESULTS: In aggregate, first-year residents' self-reported progress was consistent with that indicated by preceptors. Progress level rating on fieldnotes improved over training in both groups. Second-year residents tended to assign themselves higher ratings on self-entered assessments compared with those assigned by preceptors; however, the effect sizes associated with these findings were small. CONCLUSIONS: Although we found differences in the progress level selected between preceptor-entered and resident-entered fieldnotes, small effect sizes suggest these differences may have little practical significance. Reasonable consistency between resident self-assessments and preceptor assessments suggests that benefits of guided self-assessment (eg, support of self-regulated learning, program efficacy monitoring) remain appealing despite potential risks.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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