Teaching of anatomy in a problem‐based curriculum at the Arabian Gulf University: The new face of the museum
Bibliographic record
Abstract
The College of Medicine and Medical Sciences of the Arabian Gulf University has an undergraduate medical curriculum that uses problem-based learning as the principal teaching strategy. Teaching of anatomy comes at various places in the curriculum, and the anatomy museum serves as an important resource and engages the students in self-directed learning. Although the museum had sufficient resource materials, the emphasis on individualized instruction and self-directed learning in anatomy has resulted in the need for an effective approach and a reorganization of the facilities in the museum. Thus, we recently rearranged the museum to create 42 modules or stations (learning carrels) focusing on specific organ systems for self-study by students. Computer-assisted programs, videocassettes, ultrasound, and structured living anatomy sessions in the clinical professional skills program facilitated such an arrangement. An increased utilization by the students was observed in the reorganized museum. Thus, the museum can play an effective role in the study of anatomy through problem-based integrated learning modules.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".