EFL at Greek Second Chance Schools: Examining the Learning Needs of Muslim Adult Learners
Bibliographic record
Abstract
Discussions pertaining to minorities and their issues in education have recently been particularly heated in Greece, as changes which have occurred in Greece, Europe and at an international level, have triggered political and social turmoil and a reevaluation of cultural identities. The present paper attempts to contribute to this debate, concentrating on the Greek Muslim minority and their attempt to learn English as a foreign language (EFL) at Second Chance Schools (SCSs). The aim of this research is to explore Muslim individuals’ learning needs in relation to EFL at SCSs, the reasons which prompt them to learn the foreign language, as well as the difficulties they encounter in their quest for this knowledge. Therefore, both quantitative and qualitative methods of data collection were applied to increase the credibility and validity of the results. In addition, the issue was examined through the perspective of both learners and adult educators in order to present a more comprehensive picture of the situation. The findings have shown that Muslim learners have associated the benefits of learning English with practical matters such as communicating while travelling abroad and enhancing their professional prospects. As for the learning obstacles they face, these pertain to typical issues in adult learning such as lack of time and fatigue, as well as their deficient knowledge of the Greek language, which can interfere with their learning. Finally, both learners and instructors agree that learning English at SCSs could be upgraded with more teaching hours per week and appropriate infrastructure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".