Integration Tutorials and Seminars: A Creative Learning Approach for Occupational Therapy Curricula
Bibliographic record
Abstract
This paper, the first of two companion papers, describes a creative learning approach. Integration Tutorials and Seminars were developed to address concerns of regional fieldwork-education coordinators and preceptors about the ability of third-year student occupational therapists to integrate and apply academic and theoretical knowledge during fieldwork. This ability can be gained through experiential learning in the academic setting and is essential for the effective transfer of academic learning into the students' fieldwork-education experiences (Dale, 1994; Fidler, 1996; McCaugherty, 1991; Neistadt, 1996). The Modified Learning Model of Svinicki and Dixon (1987) was used as a template for an academic course fostering experiential learning. An important secondary goal was to nurture student self-directedness in learning using the philosophy of the Staged Self-Directed Learning Model (Grow, 1991). Case studies were used as a vehicle for engaging and challenging the students. The philosophy, guidelines and process of the Integration Tutorials and Seminars are presented and have the potential to be adapted for occupational therapy curricula around the globe.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".