Investigating the Educational and Social Factors Affecting Saudi EFL Learners' Attitudes toward Learning English
Bibliographic record
Abstract
This study aims to investigate the attitude of Saudi EFL learners toward learning English as a foreign language, their motivation, and contextual and surrounding factors affecting their attitudes positively or negatively. Out of the population that comprises students studying in levels 1 & and 2 of the graduate programs at Business College, PSAU, 216 EFL learners of Saudi Arabia were selected through a simple random sampling method. A self-designed questionnaire with partial adoption of modified items from existing studies was sent to the students to collect their responses. The quantitative approach (descriptive quantitative design) revealed that Saudi EFL students typically exhibited a high level of positivity toward English as a foreign language, and they demonstrated a high level of instrumental motivation but a lower level of integrative motivation toward English. The use of Spolsky’s (1969) and Gardner’s (1985) Second Language Learning Model and Second Language Acquisition theories respectively revealed that certain educational and social factors (e.g., English learning situation, language teachers, and parents) had an advantageous effect on Saudi EFL learners. In the same way, different social and educational factors, such as peer groups, educational settings, and educational environments, have been found negatively impacting learners' motivation and their desire to speak or learn the language. The study implies that the factors (learning physical environment, teaching material, peer groups) affecting the learners’ attitude negatively should be improved. The study would be beneficial to instructors and students in understanding the elements that impede language acquisition and assist them in attaining outstanding and effective English skills.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".