Bibliographic record
Abstract
1 PBL的源由及在台湾的萌芽 以问题为导向的学习（PBL）是近代高等学习的典范及潮流。PBL源由于1920年代商业管理的小组学习培训教育理念，于50年代以临床教案（Clinical Cases）的形式出现在医学教育。在1960年中期才由加拿大安大略省（Ontario）的McMaster大学综合了以上的二种形式融和出一种教育理念及学习方法，就成为当今的以“问题导向学习”的教育哲理；并“以学生为中心”，“以问题为教材”，“以小组为模式”及“以讨论为学习”的形式建立了世界上第一所PBL为主轴课程的医学院。至80年代PBL已传布欧美。亦影响了哈佛大学的课程设计及教育方针。90年代PBL之风才吹入了亚洲，而于12年前左右登陆台湾，最先是由台湾国立大学医学院的谢博生教授引入哈佛大学的第二代PBL；
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 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".