Student feedback experiences in a cross-border medical education curriculum
Bibliographic record
Abstract
OBJECTIVES: To determine non-Western situated health professional student experiences and preferences for feedback in workplace-based settings. METHODS: We conducted five focus groups with 27 students of Arab-origin enrolled in a Canadian-accredited cross-border pharmacy program in Qatar. Transcripts of recorded discussions were analyzed using the framework method. Hofstede's and Hall's cultural dimension models were employed to understand described feedback encounters and behaviours. RESULTS: We identified three themes associated with cultural influences on student feedback experiences, namely: 1) collectivism; 2) power distance; and 3) context. Trainees described clinical supervisors who inadequately recognized individual performance, rejected critique, and insufficiently documented feedback onto the written in-training evaluation report. Conversely, students expected specific and timely feedback, invited criticism for learning, and desired clear written commentary. CONCLUSIONS: Feedback behaviours of clinical supervisors, but not those of trainees, were consistent with local cultural norms as described by Hofstede and Hall. Instead, feedback expectations of pharmacy students in Qatar largely echo those of other trainees enrolled in professional curricula situated outside the Middle East. Principles for optimal feedback in clinical training largely arise from Western perspectives but are not necessarily universal. Our work demonstrates that practices, in part, may be subject to local socio-cultural influences. This is of particular importance in the experiential training component of cross-border medical education programs adopted by overseas institutions. Our findings also further add to the growing body of literature reporting suboptimal feedback in workplace-based learning, reinforcing the need to cultivate more student-centered practices in health professional training globally.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".