Examining Test Anxiety and Its Impact on Language Performance Among University Students: A Comparative Analysis by Gender
Bibliographic record
Abstract
This research paper examines the impact of test anxiety among English language students at the university level. The study employed a quantitative methodology, utilizing a structured questionnaire administered to 100 students from the Department of Languages and Translation, University College of Haql, University of Tabuk. The sample consisted of 50 male and 50 female participants. The study aims to examine the relationship between test anxiety and self-assessed language performance and to identify gender differences in anxiety levels. When Test anxiety considers as a prevalent issue or problem affecting students at all education levels, especially among English language students at the university level could be characterized by severe emotional, physiological, and cognitive discomfort during examinations. This may hamper the academic performance of students, diminishing their motivation and interest in studies. Data analysis covered both descriptive and inferential statistics, and revealed that the respondents text anxiety was moderate, with significant negative correlation between anxiety and self-assessment in the key language skills—listening, speaking, reading, and writing. The findings revel that, there is a moderate level of anxiety among the participants. This was reflected in the moderate levels of anxiety, as seen in various items of TAI, negative relationship between test anxiety and self-assessed language performance. This implies that students are likely to rate their language skills poorly, as their test anxiety increases, finally gender differences were evident, with female students reporting significantly higher levels of anxiety than their male counterparts. The need for a targeted preventive program, improved faculty training, and gender-sensitive support programs mirrored well in the results, indicating strategies following the principles of Cognitive-Behavioral Theory. Recommendations focused on implementing these measures to mitigate test anxiety and enhance academic performance, contributing to a more supportive educational environment.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".