A Systematic Review of Autonomous Learning in ESL/EFL in Bangladesh: A Road to Discovery Era (2009-2022)
Bibliographic record
Abstract
Learner autonomy has been a major focus of educational researchers in Bangladesh for more than a decade now. Studies in this area have generated significant themes in ESL/EFL pedagogy in Bangladesh, particularly during the last ten years or so, and the prospect looks promising. This article reviews the research pertaining to learner autonomy in Bangladesh during the years 2009-2022. The review revealed that studies related to learner autonomy in Bangladesh tend to focus on how autonomy facilitates English language teaching, examining teachers’ and learners’ attitudes, perception and readiness, factors affecting the fostering of learner autonomy, its implications, importance, and teachers’ varied roles to exhilarate learner autonomy. However, research on learner autonomy in English language teaching and learning in Bangladesh seems insignificant. During the review process, it has been evident that there is a crucial need for more in-depth empirical studies in autonomy. Moreover, there is significant lack of investigations where learners’ responses are included. Hence, this article examined the gaps, and suggestions for further studies are provided accordingly.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".