Effects of Mindfulness in the Field of English as a Foreign Language Classroom: A Literature Review
Bibliographic record
Abstract
The practice of mindfulness has its roots in medicine, where it was initially developed as a technique to assist patients in managing chronic pain. Subsequently, mindfulness was introduced to the field of education, where it is defined as the capacity to be mindful of or focus on one's internal experiences, particularly in the present moment. This paper examines the benefits of mindfulness in learning a foreign language. A review of 20 research papers on the implementation of mindfulness in EFL settings revealed that mindfulness can enhance the learning environment, improve test results and reading comprehension, increase students' willingness to communicate in English, reduce speaking anxiety, strengthen concentration, alleviate detrimental feelings or emotions, foster better health conditions, boost self-confidence, maximize foreign language teachers' self-efficacy, and strengthen students' attentional skills and emotion regulation. Consequently, it facilitates communication skills, reduces anxiety, and improves the educational environment. The research underscores the value of mindfulness as a strategy educators embrace in countries such as India, Turkey, the United States, China, and Spain. While it has yet to gain widespread adoption in Colombia, mindfulness offers a promising avenue for fostering a more positive and engaging learning experience for students and teachers. This study aims to contribute to the field of foreign language teaching by introducing new strategies that facilitate students' learning processes. As researchers, the authors seek to provide a broad perspective on this technique and its potential benefits.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".