Realizing Learner Autonomy in Pakistan: EFL Teachers’ Beliefs about Their Practices
Bibliographic record
Abstract
Learner autonomy (LA) has been a key area of interest in foreign language learning and teaching for more than three decades, but a limited space has been awarded to the investigation of teachers’ practices in fostering LA. Following an interpretive paradigm and a qualitative approach, present study intended to unearth the strategies teachers of English use to make their learners autonomous. Data were collected through semi-structured interviews with sixteen English teachers from four public universities of province Punjab. Findings revealed that, in general, teachers use teacher-centered approach while participants’ practices and use of various strategies showed their preference for the role of facilitator more than of counselor or resource. Results of this research imply that the goal of LA can be achieved through offering teachers training to make them aware of the significance of making their learners autonomous and incentives for the promotion of LA in their classroom.
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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 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".