Using Flipped Learning Model in Teaching English Language among Female English Majors in Majmaah University
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
This study aims at investigating the effect of using Flipped Learning Model in teaching English language among female English majors in Majmaah University on their achievement in two different English courses and identifying their feelings and satisfaction about flipping their classes. The study used a pre-post test design and included two experimental groups (n=62). A comparison of students’ scores in pre and post experimentation were carried to identify the effect of the model and size of improvement in students’ achievement. An analysis of students’ responses to an online questionnaire was conducted to reveal their feelings towards the flipped model. Results affirmed the hypotheses of the study and there was a significant higher improvement in students’ scores in post-tests. Students also favored the flipped learning model and had positive feelings towards it.
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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 | 0.018 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.000 | 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