English Language Anxiety and Its Effect on Students’ Mathematics Achievement
Bibliographic record
Abstract
Difficulties faced in learning a specific mathematical vocabulary are amplified through incomplete English knowledge among students who English Language Learners (ELLs). Therefore, the present study aims to investigate the relationship between English language anxiety and the mathematical achievement of EFL/ESL students who are using EMI. Mixed research method was employed to identify and understand this relationship between language anxiety and mathematics achievement in the math classroom. To collect quantitative data, a questionnaire was distributed to the students to measure their level of English language anxiety and mathematics achievement using their grades in their mathematics classes. The association between English language anxiety levels and ESL/EFL achievement in Mathematics was investigated through Pearson’s correlation test. The results showed medium levels English language anxiety among the EFL/ESL students with a mean of (2.15) and a standard deviation of (0.73). The results indicated no statistical difference in means of English language anxiety that can be attributed to the program type or graduation year (α≤ 0.05). The study concluded that English language anxiety was neutral as majority of students become nervous, when the teacher asks them unexpected questions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".