Improving Vocational and Technical Education: Comparing Flipped and Traditional Classrooms’ Impact on Learning Performance in Management Courses
Bibliographic record
Abstract
This essay examines the effectiveness of flipped classroom approaches in improving learning outcomes among first-year management students at Chinese vocational colleges. Using a quasi-experimental design, the study involved fifty classes with a total of 1,000 students, divided into experimental and control groups. The study aimed to evaluate how the flipped classroom model influences academic achievement, analytical, creative, and practical intelligence, as well as learning attitudes. It also investigated whether cognitive styles (visual vs. verbal orientation) moderated the relationship between teaching methods and learning outcomes. Results show that the flipped classroom significantly enhances cognitive learning achievements, analytical, creative, and practical intelligence, and fosters a more positive learning attitude compared to traditional methods. Notably, cognitive styles had a minimal impact on learning outcomes, suggesting that the benefits of flipped classrooms apply broadly across different learning preferences. This research enhances the understanding of effective pedagogical strategies in vocational education and underscores the flipped classroom’s potential to improve student learning experiences.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".