Chinese EAL learners’ perceptions of academic writing practices in a Canadian university
Bibliographic record
Abstract
English as an Additional Language (EAL) students’ perceptions of academic writing practices play an essential role in helping to better understand their academic literacy development processes and in meeting their actual learning needs in second language (L2) EAP writing (Leki, 1995). However, there is a scarcity of research pertaining to pre-university EAL students’ perceptions of academic writing learning experiences in English-medium higher education settings. This study investigated pre-university EAL students’ perceptions of coping strategies of academic writing practices in an EAP program in a Canadian university with case study. Findings indicated that Chinese EAL students in this study employed different coping strategies to deal with their EAP writing challenges. Also, Chinese EAL students specified their urgent learning needs in academic writing at the EAP program. Meanwhile, some pedagogical recommendations proposed to EAL academic writing instructors and EAP program administrators to impact teaching objectives and practices in pre-university EAP academic programs.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".