The Analysis of EMI Policy in Undergraduate Universities in Mainland China
Bibliographic record
Abstract
In this paper, the researcher analyses the extent to which the goals of the English as a medium of instruction (EMI) policy have been achieved in mainland China. At the national level, the implementation of the EMI policy responds to the international trend of English language education and helps to improve China’s core competitiveness in science and technology; however, the EMI policy faces some challenges, such as the obstacles to its implementation due to the educational conditions and environment, the ambiguity of whether ‘E’ in ‘EMI’ refers to ‘standard English’ or ‘English as the lingua franca’, the increase in the inequality of educational resources, and the threat posed to the traditional culture of China. From the students’ point of view, the implementation of the EMI policy improves their academic performance, but this depends to a certain extent on the students’ own English proficiency; whether or not they are able to engage in in-depth cognitive thinking in the EMI classroom varies in different teaching and learning environments; and the teacher’s level of spoken English has a non-negligible impact on the students’ academic learning. In some EMI classrooms, there is an improvement in students’ English proficiency; however, in other EMI classrooms, due to the lack of teacher-student interaction and the explanation of easier points in English, students’ English proficiency does not improve significantly. From the teachers’ perspective, teaching in English is a challenge for some, and the motivation to drive them to teach English needs to be strengthened. The researcher concludes that some practical problems in the implementation of EMI policy have hindered the realisation of its desired goals, and that the strengthening of students’ English proficiency and the assurance of teachers’ qualifications in oral English teaching may be the driving force for the effective implementation of EMI.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".