Teachers’ Voice vs. Students’ Voice: A Needs Analysis Approach of English for Acadmic Purposes (EAP) in Iran
Bibliographic record
Abstract
EAP plays a highly important role in countries where English is used mainly for academic purposes. However, EAP programs have been developed without conducting a systematic needs analysis from both the students’ and instructors’ perspective. The purpose of this study is to describe the perception that EAP students and instructors have of the problematic areas in EAP programs. A total of 693 EAP students majoring in different academic fields and 37 instructors participated in this study. Survey information included respondents’ perception the importance of problematic areas in EAP programs. The results show discrepancy between the perceptions of EAP learners in different academic fields and between learners and instructors. The study has implications for curriculum design and instructional delivery of EAP courses for college level students.Keywords: English as a foreign language, English for academic purposes, Teachers’ voice, Students’ voice, Needs analysis, EAP methodology
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".