The longitudinal case study: From Schön's model to self-directed learning
Bibliographic record
Abstract
BACKGROUND: Rapid changes observed in information technologies, medical practice, and learning methods encourage physicians to develop new updating strategies. To test its feasibility and to help physicians devise new learning and updating strategies, the knowing-in-action model developed by Schön was applied in planning and evaluating an interactive workshop. Acquisition of knowledge was tested. METHODS: The office and hospital charts of a family physician were reviewed. They were used to prepare a longitudinal case study, based on the real-life story of a hypertensive patient followed by her doctor over a period of 15 years. The clinician's approach to solving clinical problems was triangulated for credibility with general practitioners, specialists, and the information available in the literature. This longitudinal case study was used to develop an interactive educational workshop. The workshop was presented to physicians who had registered in an accredited continuing medical education event. Changes in pre- and postevent knowledge among the participants were assessed using touch pad technology to evaluate the effectiveness of this approach on the acquisition of knowledge related to management of arterial hypertension and associated clinical problems. RESULTS: A comparison of pre- and post-test data showed a significant improvement in knowledge for participants who answered all questions on both questionnaires (n = 8/37). The average score of these participants increased from 5.5 of 10 before the workshop to 8.3 of 10 after the workshop (p < .05). Participants reported a high satisfaction rate for the event. FINDINGS: A workshop using the longitudinal case study enables physicians to perceive their daily practice through a continuing education activity in which they experience the processes of reflection in action and reflection on action described by Schön. It also increases awareness of the gap between current practice and experts' recommendations and provides an opportunity to evaluate the means for bridging or closing this gap. It sensitizes the physician to patients' changing needs and prompts the clinician to reflect on the who, what, when, where, and how of learning.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".