A Study on the Relationship between Early Classroom Management Practice, Bilingual Classroom Setup, Parent' Attitudes, and English Development of Kids in Guangzhou Bilingual Kindergartens
Bibliographic record
Abstract
Under the influence of the trend of internationalization, with the increasing importance of English learning and the trend of younger English education in China, English education in private kindergartens has become one of the most discussed topics in early childhood education. It is of great significance to study the current situation of English education in bilingual kindergartens, analyze the existing problems and causes, and review and reflect on English education in bilingual kindergartens. This research adopts the questionnaire survey method to analyze and discuss the current situation of English education in bilingual kindergartens in Guangzhou, mainly from the aspects of teaching staff, classroom management, English environment creation, and parents' attitudes towards children's English education. In-depth analysis of English education in bilingual kindergartens has some problems. First, the understanding of the current kindergarten English education is biased; secondly, the level of English teachers is uneven; thirdly, the understanding of English environment creation is not thorough; fourth, the effect of classroom teaching is low; fifth. Teacher evaluation is unscientific; sixth. Lack of cooperation from family. The main reasons for the problems are analyzed from three aspects: kindergarten administrators, kindergarten English teachers and children's parents. The author hopes to help bilingual kindergartens improve the quality of English teaching through multi-dimensional research, so that more children can benefit.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".