Bibliographic record
Abstract
This study explores English academic writing in a Libyan university.The results show a number of challenges and issues that Libyan university students experience in using English for academic writing.The study suggests intervention procedures that may correct students' linguistic academic deficiencies.Using Gee (1999)'s D/discourse theory and Bourdieu's theory of habitus and field, which view writing as a social practice embedded in social activities, the study takes a purely qualitative approach, presenting data descriptions by both students and lecturers.The sample size of the investigation is eightfour lecturers and four students.The data was collected mainly through classroom observation, open-ended interviews and an analysis of students' assignment essays.The results indicate several areas of challenge for Libyan students with regard to academic writing; a lack of adequate 'scaffolding', a lack of ample time spent on authentic practice, and inappropriate immediate feedback.Findings also show a lack of teaching methods and strategies that correct syntactical and morphological errors, and a lack of skillsresearch skills.Further to this, results revealed a lack of synthesis and summary skills, referencing skillsand a lack of confidence in tackling academic writing tasks.In addition, the lack of appropriate materials to consult was a contributing factor, as was students' social and economic status.The study calls for various interventions that may assist students to acquire academic writing skills and hence develop a sense of confidence in taking on academic tasks.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".