An Empirical Study on Business English Teaching and Development in China—A Needs Analysis Approach
Bibliographic record
Abstract
<p>This paper first reviews the developmental history and status quo of Business English Program in China. Then based on the theory of needs analysis, it researches on 226 questionnaires from Business English Program students from Guangdong University of Foreign Studies to investigate the problems encountered and current situation of Business English Program in China. From the statistical analysis of the questionnaires, it finds: (1) employment and interest are the main reasons that students choose Business English as their major, but the current Business English teaching materials haven’t fully considered student’s demands for vocational requirements; (2) it should take into account both the learners’ and societies’ needs in Business English curriculum arrangement to increase the number of business-related courses appropriately; (3) students generally agreed that they lacks business knowledge and skills, so Business English courses should focus on cultivating the practical business skills; (4) Business English teaching materials should always be practicality oriented and targeted and communicative; (5) in order to improve teaching effectiveness, Business English teachers should consciously adopt different teaching methods targeted for different teaching content during the teaching process; (6) teachers’ morality, knowledge, teaching style and mutual relationship with students can be further enhanced to meet the needs of students.</p>
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".