Understanding the Well-Being Literacy of EFL Learners: Towards a Framework of Learners’ Knowledge and Skills
Bibliographic record
Abstract
Well-being has been recognized as a basic human right, a core determinant of success in education, and a skill that can be developed. In language education, the literature suggests that higher well-being is likely to lead to more classroom engagement and ultimately greater success for learners. For English language teachers, there is a need to understand what learners know about well-being, what kinds of support they feel they need, and how best to integrate such support into regular language teaching practice. This paper reports on a qualitative study using focus group data that set out to understand the well-being literacy of a group of 42 Austrian learners of English as a foreign language (EFL) in their final year of school. The findings reveal five categories in which learners demonstrated knowledge of well-being: conceptual understanding of well-being, factors impacting well-being, coping strategies, the role of systemic factors, and issues in the English language teaching context specifically. Based on analysis of these data, we present an initial practical framework for evaluating and guiding EFL student well-being literacy development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".