baseada na ABP, essa experiência mostra que tal metodologia pode ser utilizada de forma bem sucedida em algumas disciplinas do currículo. Palavras-Chave: Aprendizagem Baseada no Problema, Raciocínio Clínico,
Bibliographic record
Abstract
Problem Based Learning (PBL) was introduced as a new learning methodology at McMaster University in Canada in the 1960’s. Since then, PBL became an important alternative to traditional education models. Objective: to describe an experience of using PBL in a course of the undergraduate Occupational Therapy program]me at the Federal University of Minas Gerais. Methods: On the second semester of 2007, the discipline “Clinical reasoning in Occupational Therapy for Children” was offered to undergraduate students. The course was based in case studies and its aim was to develop the student’s clinical reasoning to conduct occupational therapy interventions for children. Results: Thirteen students volunteered to participate in the course; they were divided in two tutorial groups, each one tutored by a graduate student of the postgraduate Rehabilitation Sciences Programme, and both oriented by a professor. At the beginning, the students had difficulties with the new methodology, because they were not used to some PBL’s features. Throughout the semester, the students showed more independent performance on gathering and appraising information and reported, thorough a questionnaire responded at the end of the course, greater learning than with the traditional educational methods. Conclusion: PBL is an important alternative to traditional educational methods, but it requires appropriate physical and personnel structure, conditions that are difficult in Brazilian public universities. If it is not possible to construct the whole curriculum based on PBL, this experience shows that this methodology can be used successfully in just some courses.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".