The Effect of EFL Teachers’ Training in Rural West China: Evidence From Phonics-oriented Program
Bibliographic record
Abstract
China has launched a nation-wide project of learning English as a “core” subject starting from the third grade in primary schools after the Ministry of Education (MOE) issued National English Curriculum Standards for Compulsory Education at the beginning of this century. However, EFL teachers are far from sufficient in rural schools, and thus students are in a more disadvantageous position compared to their peers in the urban area. To meet this need, many Zhuangang teachers are employed after being trained. This study examined a phonics-oriented training program in which scholars and practitioners cooperated to train EFL teachers and prospective trainers in rural west China. The current study collected data about EFL teachers’ perceptions on the effect of this program and student achievement. The results showed that the training program was quite effective with EFL teachers regarding the program as helpful and students obtaining significantly better scores. These findings indicate that phonics-oriented professional support system is a good way to make teacher development sustainable in the long run.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".