Still Not Clear? Exploring the Impact of Clarifying Assessment Items on Assessor Cognition in Medical Education
Bibliographic record
Abstract
Assessment variability in formative assessment occurs when assessors observing a trainee performing the same task evaluate the trainee differently. One major contributor is uncertainty regarding assessment criteria, and efforts to clarify criteria are not always successful. This study explores the cognitive processes that occur in assessors' minds when assessment criteria are clarified. We interviewed clinical teaching faculty from one residency program in a single institution regarding their perceived expectations of select assessment items before and after providing clarifying criteria and how the clarification changed their perception. We analyzed the data thematically. Assessors' cognitive interaction with assessment clarification is a function of four factors: 1) Assessors' fixed ideation, 2) Content of the criteria themselves, 3) Context and setting of criterion interpretation, and 4) Interaction between the assessor and the trainee. The cognitive effects of clarifying assessment items depend not only on the assessor and criteria but additionally on their interactions within a professional and academic context. The complexity and multifactorial nature of assessment variability may explain the difficulty in mitigating criterion uncertainty.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".