Problem-based Learning and Theories of Teaching and Learning in Health Professional Education
Bibliographic record
Abstract
Although problem-based learning (PBL) has been linked to several theories of teaching and learning, how these theories are applied remains unclear. The objective of this paper is to explore how theories of teaching and learning relate to and can inform problem-based learning within health professional education programs. We conducted a scoping review on current theories of teaching and learning and considered their relevancy to the problem-based learning approach. The findings suggest that no single theory of teaching and learning can fully represent the complexity of learning in PBL. Recognizing the complexity of the PBL environment and the fluidity between theories of teaching and learning, we proposed eight principles from across 11 theories of teaching and learning that can inform how PBL is operationalised in university-based health professional education: 1) Adult learners are independent and self-directed; 2) Adult learners are goal oriented and internally motivated; 3) Learning is most effective when it is applicable to practice; 4) Cognitive processes support learning; 5) Learning is active and requires active engagement; 6) Interaction between learners supports learning; 7) Activation of prior knowledge and experience supports learning; and 8) Elaboration and reflection supports learning. These eight principles provide the foundation for curriculum design recommendations relevant to PBL within university-based education programs. Specifically, our findings suggest that active engagement and interactions should be encouraged, that students should be prompted to activate their prior knowledge and experiences, and that elaboration and reflection on learning is critical. The small group format of PBL can facilitate this engagement if students question each other, consider alternative perspectives, and are actively involved in setting learning objectives. Further research is needed to develop the empirical basis for these principles and examine if PBL is an effective approach for implementing these principles.
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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 | 0.019 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.027 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".