Impact of state-trait anxiety on the foreign language anxiety: Mediating role of mindfulness
Bibliographic record
Abstract
Issues related to the acquisition of a foreign language can result in negative psychological consequences further hindering the learning of the students. Such as anxiety among students tends to result in negative outcomes such as poor learning. Accordingly, it becomes crucial to deal with such issues to better foster the learning context of the foreign language. Thus, the purpose of this study was to test the influence of the state-trait anxiety and foreign language anxiety relationship. Additionally, mediating role of mindfulness was also examined. Aligned with the aim of the study positivism research philosophy was adopted and a quantitative-deductive approach was followed. All the variables were measured by adapting the questions from previous studies and a total of 433 students from 32 schools located in the Selangor state responded to the questionnaire distributed. The study results revealed that state-trait anxiety among the students tends to result in mindfulness among the school students and it is also found to influence the foreign language anxiety. Additionally, results also revealed that the state-trait anxiety and foreign language anxiety relationship is significantly mediated by the mindfulness of the school students. The results established that highly mindful students tend to have better learning in foreign language learning as compared to individuals with low mindfulness. From the results, variables showed symbiotic relationships and hence can be used as a model to develop a holistic personality of the learners in the future.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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".