Exploring the Impact of Teacher Role Changes in the Flipped Classroom Model on the Critical Thinking Abilities of University Students
Bibliographic record
Abstract
This study investigates the impact of teacher role changes within the flipped classroom model on the critical thinking abilities of Canadian university students. Employing a mixed-methods research design, the study combines quantitative data from pre- and post-tests using the California Critical Thinking Skills Test (CCTST) with qualitative insights from student and teacher interviews. The quantitative analysis revealed statistically significant improvements in students’ critical thinking abilities in flipped classroom settings, particularly in analysis, inference, and evaluation skills, indicating a medium to large effect size (η² = 0.111). Qualitative findings underscore the importance of increased student engagement, enhanced learning environments, the value of collaborative learning, and the pivotal role of teacher support and feedback in facilitating critical thinking development. Integrating these findings, the study offers a multifaceted view of how strategic pedagogical shifts—specifically, adopting more facilitative and supportive roles by teachers—can significantly enhance critical thinking in higher education. This research contributes to the literature on educational strategies, advocating for the broader adoption of flipped classroom models as a means to foster active, student-centered learning and critical thinking skills.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".