A Schema–Theory Based Study on the Improvement of the College Students’ English Writing
Bibliographic record
Abstract
College English Test-Band 4 is of great importance for non-English major students. However, some related survey shows that students’ writing competence in CET4 is far from satisfactory. Thus improving students’ writing ability has become the urgent task for English teachers and language scholars. The author carries on a ten-week empirical research on the application of schema theory to non-English majors’ EFL writing teaching. Before the experiment, 120 freshmen of non-English majors are randomly chosen as a sample. The subjects are divided into two groups. One is the control group, and the other is the experimental group. The former receives traditional English writing teaching mode. The latter receives schema-theory based writing training. The author goes on to make statistical treatments with questionnaires, the interview, the pretest and posttest in writing. The result shows: Schema-theory based writing training has a great effect on non-English majors’ writing ability, which also helps college students change their writing habits and writing mode. Their linguistic accuracy, content correctness and formal appropriateness have been achieved after schema-based writing training. The participants in experimental group hold a positive attitude toward the new way of writing teaching.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".