Crossing boundaries in interprofessional education: A call for instructional integration of two script concepts
Bibliographic record
Abstract
Clinical work occurs in a context which is heavily influenced by social interactions. The absence of theoretical frameworks underpinning the design of collaborative learning has become a roadblock for interprofessional education (IPE). This article proposes a script-based framework for the design of IPE. This framework provides suggestions for designing learning environments intended to foster competences we feel are fundamental to successful interprofessional care. The current literature describes two script concepts: "illness scripts" and "internal/external collaboration scripts". Illness scripts are specific knowledge structures that link general disease categories and specific examples of diseases. "Internal collaboration scripts" refer to an individual's knowledge about how to interact with others in a social situation. "External collaboration scripts" are instructional scaffolds designed to help groups collaborate. Instructional research relating to illness scripts and internal collaboration scripts supports (a) putting learners in authentic situations in which they need to engage in clinical reasoning, and (b) scaffolding their interaction with others with "external collaboration scripts". Thus, well-established experiential instructional approaches should be combined with more fine-grained script-based scaffolding approaches. The resulting script-based framework offers instructional designers insights into how students can be supported to develop the necessary skills to master complex interprofessional clinical situations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".