The Development and Implementation of New Assessment Tools for the Surgical Clerkship Rotation
Why this work is in the frame
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Bibliographic record
Abstract
<ns4:p>This article was migrated. The article was marked as recommended. Innovation: We developed two new rubrics with explicit behavioural anchors to assess students in the Queen's undergraduate medical education (UGME) surgery clerkship rotation. These rotation rubrics, complemented by a new ambulatory clinic encounter card, improved the quality, consistency, and timeliness of feedback for clerks from faculty preceptors. This innovation was introduced during a comprehensive workplace-based assessment re-design being undertaken in the Department of Surgery as part of the transition to a post-graduate competency-based medical education (CBME) system for post-graduate education (PGME). The core UGME working group, comprised of a faculty surgeon, assessment consultant, and a surgical resident, selected terminology and designed the tool visual structure to be similar to the new post-graduate assessment tools, since most preceptors supervise learners in both programs. This consistency enhanced buy-in from faculty and ensured a smooth transition to the use of the new UGME tools. Development: The new assessment process was developed and piloted in three phases: (1) development of an assessment system based on rubrics with explicit behavioural descriptors as the key assessment tools; (2) implementation of a pilot study to establish the acceptability and feasibility of the use of these rubrics, with iterative revisions based on stakeholder feedback; and (3) development of a validity argument for the use of these assessment tools. The latter is scheduled for 2018. Outcomes: The use of these rotation behaviour-anchored rubrics and corresponding ambulatory clinic encounter card has greatly improved the mid- and final-rotation feedback provided to students on the Surgery Clerkship. The concrete, descriptive information provided by the rubrics allows the course director to provide specific feedback during rotation exit meetings. The course director has the ability to clearly articulate to students the areas where they have met (or exceeded) the expected level of competency, as well as areas which require additional attention.</ns4:p>
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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 | 0.003 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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