Mixed-Method Research On EFL Graduate Students’ Academic Writing Practices
Bibliographic record
Abstract
This study aims to identify (i) how EFL graduate-level students at various Turkish universities regard the level of difficulty in terms of the different sections of a scholarly work in their academic writing practices, (ii) whether their perceptions concerning the difficulty of the various sections show a significant difference depending on their demographics, (iii) the solutions they employ when they are challenged with difficulties in academic writing and (iv) their views about the process of academic writing in general. Data from 34 graduate EFL students were reported. The study adopted a mixed-method research design, and the data were collected with Academic Literacies Questionnaire (ALQ) (Chang, 2006; Evans & Green, 2007). The participants also responded to open-ended questions about the challenges they face in academic writing and their solutions. The results revealed that EFL graduate students had problems with academic conventions, and found expressing themselves succinctly problematic. However, they were familiar with the mechanics of the target language.
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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 | 0.025 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".