An Empirical Study on the Application of Multi-modal Teaching Model on English Writing Teaching in China Senior High School
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
Recently, Multi-modal teaching has attracted much attention in the field of second-language writing. Previous studies paid great attention to the pedagogical effects of this teaching model on the writing competence of college students in China. Less investigation focused on the writing performance of Chinese senior high school students. This study aims to investigate the influence of Multi-modal teaching model on English writing competence in terms of writing score, language performance, and students’ writing attitudes. The research instruments consist of two English writing tests, questionnaires and an interview. The research results showed that Multi-modal teaching model can significantly improve learners’ writing competence. Meanwhile, the attitudinal survey indicated that Multi-modal teaching model has a positive influence on senior high school English learners’ writing competence and writing interest.
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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 | 0.003 | 0.001 |
| 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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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