Evaluation on Degree and Result of Bilingual Education of Business Courses in GDUFS
Bibliographic record
Abstract
From the connotation of bilingual education in higher education in China, this paper analyzes the factors that may affect the quality and result of bilingual education, such as faculty and students’ English level, teaching materials, curriculum system, classroom instruction, teaching quality control, as well as incentives and other factors. The paper focuses on Fuzzy-AHP model as a university bilingual education quality evaluation system, and build an evaluation index system for quality control of bilingual teaching. It also conducts quantitative analysis using analytic hierarchy process and fuzzy comprehensive evaluation on the degree of the bilingual education of business courses in Guangdong University of Foreign Studies (GDUFS), China. By selecting evaluation indicators and using analytic hierarchy process, the paper determines corresponding weight of the indicators. It also establishes sets of standard on evaluation and fuzzy relationship matrix, and conducts an empirical study on the degree of bilingual education of business courses in GDUFS. The paper has certain theoretical and practical significance for bilingualism in higher education in China.
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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 | 0.003 |
| 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) | 0.001 | 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 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".