Examining the Reliability of Scores From a Performance Assessment of Practice-Based Competencies
Bibliographic record
Abstract
The purpose of this study was to examine the reliability and sources of score variation from a performance assessment of practice competencies within an occupational therapy program. Data from 99 students who participated in a practical exam were examined. A generalizability analysis of analytic, total, and overall holistic scores was completed accounting for the nested design. The results demonstrated that rater pairs produced highly reliable (i.e., G > 0.93, ϕ > 0.90) overall holistic, total, and analytic scores. In all scoring scenarios, student variation accounted for the largest percentage of total variance with less variation attributable to raters. However, the interaction-error term accounted for the second most variation within the system. Findings from this study suggest possible differences in rater behavior raising questions for future research around the processes raters use to generate holistic versus analytic scores.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".