Development of a clinical reasoning tool to support professional education
Bibliographic record
Abstract
Introduction: Anecdotal evidence from occupational therapy professional educators suggests that some students have difficulty articulating the clinical reasoning used to support their practice. Clinical reasoning, or professional reasoning as it is now frequently termed, describes the thinking processes used by occupational therapists when planning, conducting and reflecting on practice. Clinical reasoning is the conduit by which tacit knowledge as well as the multiple layers of thought processes can be explicated and shared. Students can use clinical reasoning as a bridge to assist them in applying theoretical knowledge in practice and to communicate with their educators. Objective: To describe the development and use of a Clinical Reasoning Tool to support students and professional educators during professional education experiences. Approach: The paper will describe how clinical reasoning literature, and specifically the Hierarchical Model of Clinical Reasoning, informed the development of the Tool. The Tool was developed to align with commonly used occupational therapy models, such as the Model of Human Occupation and the Canadian Practice Process Framework, thus prompting students to reason at each facet or stage of therapy. The paper will also examine how the Tool can be used in conjunction with Gibbs’ Reflective Cycle. A case study will illustrate how a student could use the Tool on placement. Practice Implications: This paper presents a Tool that can be used by university educators to assist students prepare for placement, and by professional educators to support student learning in a range of environments. The Clinical Reasoning Tool enables students to make informed links between theory and practice. Conclusion: The Clinical Reasoning Tool was developed in response to professional educator feedback to support students on placement. The benefits of the Tool include promotion of a shared language between educators and students and support for deep learning during professional education experiences.
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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 | 0.017 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".