Self-esteem of Saudi Learners and Its Relationship to Their Achievement in English as a Foreign Language
Bibliographic record
Abstract
This study examined the concept of language self-esteem among 263 Saudi learners of English as a foreign Language (EFL) and its association with their achievement in this language. The study utilized a questionnaire survey for data collection and descriptive statistical analyses (e.g. mean, standard deviation, correlations) and a t-test for data analysis. The findings of the study revealed a strong positive correlation (r = 0.414) between learners' self-esteem and their EFL achievement. In addition, participating learners demonstrated low levels of self-esteem (M = 2.94 (out of 5), SD = .44); and low language achievement (M = 62.80 (out of 100), SD = 12.75). There were also no significant differences between male and female learners in terms of both their self-esteem and EFL achievement. The findings derived from this study acknowledge the vital need for all the partners of EFL teaching/learning process in Saudi Arabia to find practical solutions to build and promote Saudi EFL learners' self-esteem for learning the English language. Based on these findings, some suggestions on how to put learner's self-esteem into practice in order to ensure optimal EFL learning outcomes as well as other points for possible future self-esteem research are presented in the concluding section of this paper.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".