Exploring the Relationship between Writing Apprehension and Writing Performance: A Qualitative Study
Bibliographic record
Abstract
Writing skill is seen as a cornerstone of university students’ success in both academic and career life. This qualitative study was conducted to further explore the teachers’ and students’ perceptions on the relationship between writing apprehension and writing performance, contributing factors of writing apprehension, and strategies to reduce writing apprehension. Semi-structured interviews were conducted to get more in-depth information from two respondents: one experienced instructor of teaching writing at the Centre for Languages and Pre-University Academic Development (CELPAD), International Islamic University Malaysia, and another, a graduate student who was reported to having a high level of writing apprehension using Daly and Miller’s (1975) questionnaire on writing apprehension. Thematic analysis approach was used for data analysis. Both respondents were convinced that writing apprehension has a negative influence on students’ writing performance; the sources of contributing factors could be students, instructors, and teaching learning setting; and writing apprehension could be reduced through suggested strategies. It is recommended that instructors should be more aware of students’ problems in the writing skill.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".