Associations between an open-response situational judgment test and performance on OSCEs and fieldwork: implications for admissions decisions and matriculant diversity in an occupational therapy program
Bibliographic record
Abstract
BACKGROUND: Casper, an online open-response situational judgement test that assesses social intelligence and professionalism [1], is used in admissions to health professions programs. METHOD: This study (1) explored the incremental validity of Casper over grade point average (GPA) for predicting student performance on objective structured clinical examinations (OSCEs) and fieldwork placements within an occupational therapy program, (2) examined optimal weighting of Casper in GPA in admissions decisions using non-linear optimization and regression tree analysis to find the weights associated with the highest average competency scores, and (3) investigated whether Casper could be used to impact the diversity of a cohort selected for admission to the program. RESULTS: = 3.2%). Non-linear optimization and regression tree analysis indicate the optimal weights of GPA and Casper for predicting performance across fieldwork placements are 0.16 and 0.84, respectively. Furthermore, the findings suggest that students with a slightly lower GPA (e.g., 3.5-3.6) could be successful in the program as assessed by fieldwork, which is considered to be the strongest indicator of success as an entry-level clinician. In terms of diversity, no statistically significant differences were found between those actually admitted and those who would have been admitted using Casper. CONCLUSION: These results constitute preliminary validity evidence supporting the integration of Casper into applicant selection in an occupational therapy graduate program.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".