The Effects of CMC Applications on ESL Writing Anxiety among Postgraduate Students
Bibliographic record
Abstract
This study investigates the effects of the CMC applications on the ESL/EFL writing anxiety. This is a descriptive study using a mixed-method that adopted both quantitative and qualitative approaches. Three instruments were employed to answer the research questions of the current study which are Second Language Writing Anxiety Inventory (SLWAI), Semi-structured Interview, and Documents Observation. The respondents consisted of twenty eight post-graduate ESL/EFL students who enrolled in the elective course of Computer Application in ESOL (SKBI6133) at the Faculty of Social Sciences and Humanities, School of English Language Studies, National University of Malaysia (UKM). The findings showed a significant change in their attitudes toward writing after they had engaged in writing process approach and CMC applications in the course. In addition, the respondents perceived that there was a positive effect of on their writing performance and improvement on their writing anxiety level particularly through the use of CMC applications.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".