Enhancing critical thinking through active learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Today the Framework for 21st Century Learning developed by the Partnership for 21st Century Learning (P21) is widely recognized and has been used in the U.S., Canada and New Zealand. P21 defines and illustrates the skills and knowledge students need and states that critical thinking is fundamental for twenty-first century success and essential for success in an academic context. The Organization for Economic Co-operation and Development (OECD) also values the importance of cultivating critical thinking. However, critical thinking is not a part of the EFL curriculum in Japan, and lessons are not focused on the development of meta-cognitive strategies. How do we help students learn foreign languages and twenty-first Century Skills at the same time? Active learning and content and language integrated learning (CLIL) offer such a learning environment where learners enhance their cognitive skills and gain knowledge while they are learning content and language. This paper reports on a study that explores how active learning with CLIL instruction helps Japanese EFL learners to develop critical thinking skills. In the author’s student-centered instruction based class, critical thinking was stimulated with questions based on the revised Bloom’s taxonomy to develop lower and higher order thinking skills while various scaffolding activities were provided. Pretest-posttest results from the Critical Thinking Disposition Scale (CTDS) and the Cornell Critical Thinking Test (CCTT) Level Z were compared to determine to what extent, if any, EFL learners developed critical thinking disposition and skills through active learning in CLIL classes. The results of the CTDS and CCTT suggest that active learning has value for increasing critical thinking.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it