Domains of effective teaching process students perspectives in two medical schools
Bibliographic record
Abstract
BACKGROUND: There has been little systematic investigation of student belief about the characteristics of the optimum process for clinical bedside teaching. AIMS: The intent was to identify the most important characteristics of the bedside teaching experience from the perspective of two groups of students, one from Oman and the other from Canada. METHOD: Students were asked to complete a questionnaire about their concept of the ideal process of bedside teaching. Their answers were analyzed using factor analysis. RESULTS: Answers provided by the students was consistent with the presence of six domains. These corresponded to Preparation, Introduction, Experience, Summary, Explanation, and Conclusion. 'Preparation' involves consideration of the patient and the knowledge level of the learners, 'Introduction' involves effective communication, and 'Experience' means the need for the students to be actively involved in the history and physical examination. The remaining three domains deal with the need to provide a summary and elaboration as well as advice and feedback. These 6 factors explained 60% of the total variance. CONCLUSIONS: While these areas still need to be defined more closely, the application of these six domains to the structure of the bedside teaching experience is likely to result in improved student learning.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 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".