A cross-institutional examination of readiness for interprofessional learning
Bibliographic record
Abstract
This paper examines the readiness for and attitudes toward interprofessional (IP) education in students across four diverse educational institutions with different educational mandates. The four educational institutions (research-intensive university, baccalaureate, polytechnical institute and community college) partnered to develop, deliver and evaluate IP modules in simulation learning environments. As one of the first steps in planning, the Readiness for Interprofessional Learning Scale was delivered to 1530 students from across the institutions. A confirmatory factor analysis was used to expand upon previous work to examine psychometric properties of the instrument. An analysis of variance revealed significant differences among the institutions; however, a closer examination of the means demonstrated little variability. In an environment where collaboration and development of learning experiences across educational institutions is an expectation of the provincial government, an understanding of differences among a cohort of students is critical. This study reveals nonmeaningful significant differences, indicating different institutional educational mandates are unlikely to be an obstacle in the development of cross-institutional IP curricula.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".