Effects of the Flipped Classroom Model on Students’ Self-Directed Learning Readiness and Attitudes Towards the English Course
Bibliographic record
Abstract
This study aims to investigate the effects of the flipped classroom model on ninthgrade students’ self-directed learning readiness and attitudes towards the English course and identify how the flipped classroom method affects students’ self-directed learning readiness and attitudes towards the English course as well as the potential reasons for these. The study adopted an explanatory sequential design, one of the mixed method research designs. In line with the mixed method approach, quantitative phase of this study utilized pretest-posttest control group quasi experimental design, and the qualitative phase included focus group interviews to collect data. Quantitative data were collected using the “Self-directed Learning Readiness Scale” and “Attitudes towards the English Course Scale”. The study was conducted with 46 ninth grade students who were enrolled in Vocational and Technical Anatolian high school in a city located in the southern part of Turkey in the 2015-2016 education year. Results showed a significant difference between the experimental and control group in terms of self-directed learning readiness and attitudes towards the English course in favor of the experimental group students.According to qualitative findings, the flipped classroom method had positive contributions to students’ self-directed learning readiness and attitudes towards the English course. Quantitative and qualitative findings were found to be parallel with each other.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".