Globalization of Problem‐based Learning (PBL): Cross‐cultural Implications
Bibliographic record
Abstract
Problem-based learning (PBL) is essentially a learning system design that incorporates several educational strategies to optimize student-centered learning outcomes beyond just knowledge acquisition. PBL was implemented almost four decades ago as an innovative and alternative pathway to learning in medical education in McMaster University Medical School. Since then, PBL has spread widely across the world and has now been adopted globally, including in much of Asia. The globalization of PBL has important cross-cultural implications. Delivery of instruction in PBL involves active peer teaching-learning in an open communication style. Consequently, this may pose an apparent serious conflict with the Asian communication style generally dominated by a cultural reticence. However, evidence available, especially from the PBL experience of some senior Korean medical students doing an elective in the University of Toronto Medical School and the cross-cultural PBL experience initiated by Kaohsiung Medical University, strongly suggests creating a conducive and supportive learning environment for students learning in a PBL setting can overcome the perceived cultural barriers; that is, nurture matters more than culture in the learning environment. Karaoke is very much an Asian initiative. The Karaoke culture and philosophy provide a useful lesson on how to create a conducive and supportive environment to encourage, enhance and motivate group activity. Some key attributes associated with Asian culture are in fact consistent with, and aligned to, some of the basic tenets of PBL, including the congruence between the Asian emphasis on group before individual interest, and the collaborative small group learning design used in PBL. Although there are great expectations of the educational outcomes students can acquire from PBL, the available evidence supports the contention the actual educational outcomes acquired from PBL do not really match the expected educational outcomes commonly intended and specified for a PBL program. Proficiency in the English language can pose serious problems for some Asian medical schools, which choose to use English as the language for discussion in PBL tutorials. A novel approach that can be applied to overcome this problem is to allow students to engage in discussions using both their native language as well as English, a highly successful practice implemented by the University of Airlangga, Surabaya, Indonesia. As PBL is a highly resource-intensive pedagogy, Asian medical educators need to have a clear understanding of the PBL process, philosophy and practice in order to be able to optimize the educational outcomes that can be derived from a PBL curriculum.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".