Perceptions of the Effect of an EAP Course on English Self-efficacy and English Proficiency: Voices of International Students in China
Bibliographic record
Abstract
The English language has become an essential means for communication and studies for international students globally. With the increasing number of international students trooping to China to study diverse courses which are taught in the English medium, there is a need to address challenges faced by international students from non-native English speaking countries. The study adopted an embedded mixed-method approach where face-to-face interviews and focus group discussions were conducted on freshmen international students taking English for Academic Purposes (EAP) in a specific faculty of a university in China. The interviews were supplemented by the Questionnaire of English Self-Efficacy (QESE) to measure their perceived English self-efficacy after the course. An online questionnaire on English Course Evaluation (ECE) was used to measure the students’ assessment of the course. The findings of the study offer insights into the effect of the intervention, challenges faced by students during the course, and suggestions on things to consider during the implementation of English courses for non-native English students in the future.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".