English Language Speaking Anxiety among Afghan University Students
Bibliographic record
Abstract
Background/purpose: English language plays an important role in Afghanistan higher education. Proficiency in English as the language of communication is becoming progressively important for the development of higher education. However, speaking in English is one of the anxiety provoking skills for most of Afghan learners. This study therefore aims to investigate Afghanistan undergraduate English and literature students’ perceptions on foreign language speaking anxiety, and its components of communication apprehension (CA), fear of negative evaluation (FNE) and test anxiety (TA). Method: An adapted version of Foreign Language Classroom Anxiety Scale (FLCAS) and an interview protocol were used to investigate 302 Afghan students’ foreign language anxiety. Results/conclusion: The findings suggested that the students experienced a moderate level of anxiety. The female students had higher level of foreign language anxiety (FLA) than male students. The study further revealed that CA was the highest factor which contribute to students’ FLCAS. The study found no statistically significant differences between the university location and components of FLA. This means that the students either from Kabul as the capital or from Bamyan as a central province experienced FLA. Furthermore, the components of FLA significantly correlated to each other. The findings suggest facilitating short and long-term training for both teachers and students to employ effective strategies on reducing the level of anxiety in English language classes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".