Student Perception of the Integrated PBL MBCHB-III Program Curriculum in a Medical University
Bibliographic record
Abstract
Introduction: Integrated PBL is now an accepted method of teaching the medical curriculum. The objective of this study was to determine MBChB-III students’ perceptions about some key aspects related to our integrated PBL curriculum.Methods: This was an anonymous, questionnaire based, descriptive study, involving the Walter Sisulu University MBChB year 3 students as participants. The short questionnaire focused on key student perception areas related to integrated PBL curriculumResults: More than half of the students felt that the curriculum enhanced analytical skills, and was reasoning and learning centered. 29.5% of the students felt that the desired goals and objectives were not clear enough. About 90% felt that they felt they could recognize discipline interrelations. While 61.7% of students felt that the curriculum facilitated active learning opportunities, more than 70% felt that it increased the workload and stress levels. About half of the students expressed overall satisfaction with the level of content integration.Conclusion: Students generally presented favorable perceptions of the integrated MBChB-III PBL curriculum. There were concerns about the associated heavy workload and stress. Student counseling with respect to time and stress management coupled with improvements in curriculum design would be helpful in addressing the issue.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".