PROBLEM BASED LEARNING APPLIED TO PRACTICE IN MEDICAL SCHOOLS IN BRAZIL: A MINI-SYSTEMATIC REVIEW
Bibliographic record
Abstract
ABSTRACT Background Active learning is a well-established educational methodology in medical schools worldwide, although its implementation in Brazilian clinical settings is quite challenging. The objective of this study is to review the literature in a systematic manner to find and conduct a reflective analysis of how problem-based learning (PBL) has been applied to clinical teaching in medical schools in Brazil. Material & methods A systematic literature search was conducted in three databases. A total of 250 papers related to PBL in Brazilian medical schools were identified through the database searches. Four studies were finally selected for the review. Results Four fields of medicine were explored on the four selected papers: gynecology/family medicine, medical semiology, psychiatry, and pediatrics. Overall, all the papers reported some level of strategic adaptability of the original PBL methodology to be applied in the Brazilian medical school’s curricula and to the peculiar characteristics specific to Brazil. Conclusion PBL application in Brazilian medical schools require some level of alteration from the original format, to better adapt to the characteristics of Brazilian students’ maturity, health system priorities and the medical labor market.
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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 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".