Review of Foreign Language Anxiety Relationship with Language Achievement of EFL Students in Saudi Arabia
Bibliographic record
Abstract
This study is conducted to evaluate learning and teaching English as a foreign language (EFL) in the Kingdom of Saudi Arabia (KSA) since English is still treated as a foreign language. Despite the prevailing high-level anxiety in Saudi learners of the English language, there are limited researches available to study the impact of language anxiety on the achievement of the student in a particular language. This literature search study explored the underlying causes and impacts of foreign language anxiety (FLA) and then studied these impacts on the language achievement of Saudi students in EFL classrooms in KSA. Credible academic researches and conference papers are critically reviewed in the context of the relationship between foreign language anxiety and language achievement of EFL students in Saudi Arabia. The findings of the review revealed that government initiatives and exposure to globalization in Saudi Arabia, students are encouraged to get expertise in English through EFL courses. However, the review of literature demonstrated that Saudi students experience anxiety while learning English as an unknown language. Additionally, the level of understanding in students of FLA negatively affected their accomplishment. Therefore, the collaborative strategies in classrooms are needed with complete participation of language instructors and favourable environment with positive competition building strategies encourage EFL students to enhance learning.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".