Intercultural Competence in EFL Learning: Implications for Sustainable Development
Bibliographic record
Abstract
In today's globalized world, the development of intercultural competence is essential for the learners of English as a Foreign Language (EFL). This paper aims to investigate the significance of intercultural competence in relation to sustainable development and explore the challenges faced by EFL learners in acquiring this essential skill in the Egyptian and Saudi universities. The study is based on the premise that improving intercultural competence among EFL learners can significantly contribute to sustainable development. Intercultural competence fosters mutual understanding, tolerance, and respect for cultural diversity, laying the foundation for harmonious and productive global interactions. To improve intercultural competence in EFL learners in the Egyptian and Saudi universities, the study conducted an interview survey with 30 faculty members, English department heads, program designers, and stakeholders. Results emphasize the importance of incorporating authentic intercultural experiences into EFL curricula and providing learners with practical opportunities to develop their intercultural competence. The study highlights the necessity of integrating intercultural competence into EFL materials to equip EFL learners with the requirements of sustainable development and better addressing the globalization challenges. Educators, program designers, policymakers, and researchers are finally recommended to promote intercultural understanding and sustainable development through EFL education.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".