Reading and Writing Learning Strategies for Low English Proficiency Students at a Private University in China
Bibliographic record
Abstract
This study aimed at applying English reading and writing strategies’ training to improve the low English proficiency students’ competence of English reading and writing. It was a quasi-experiment design. In total, 70 non-English major undergraduates at a private university in China participated in the research, 35 students in the experimental group and the rest 35 students in the control group. The intervention of English reading and writing strategies training was applied to the experimental group over a 24-lesson period in 6 weeks. The control group received an English reading and writing course without the intervention in the same period of the class schedule. Meanwhile, this study applied SILL and PET to the pre-test and the post-test, and used statistical analysis to do data analysis. The result of a detailed one-way ANCOVA showed that the intervention of English reading and writing strategies training in the experimental group had a significant improvement in English reading and writing skills.
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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 | 0.000 | 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 | 0.001 |
| 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".