The Role of Teachers in Promoting Learner Autonomy in Secondary Schools in Saudi Arabia
Bibliographic record
Abstract
Today, learner autonomy is considered as a desirable goal in language education. The movement towards learner-centered approaches has resulted in more emphasis on the benefits of learner autonomy in the success of language education. The objective of the study was to investigate the roles of the teachers in promoting learner autonomy in Saudi EFL secondary school, with emphasis on the important roles of the facilitator, counselor, resource and manager. A survey questionnaire was used in this study to elicit the responses of 60 EFL teachers in Riyadh during the academic year 2015-2016. The findings of this study revealed that English language teachers often encouraged autonomous learners in their classrooms. They usually implemented different teaching strategies, which demonstrated the four roles: facilitator, counselor, resource and manager. Moreover, the findings showed that teachers were hindered by some difficulties including learners’ lack of independent learning skills, rules and regulations applied in schools, and teachers’ lack of basic strategies to encourage autonomous learning. Furthermore, the teachers believed that approaches such as teachers’ continuous reflection and analysis of their own teaching process, reducing the school rules that restrict the teachers’ independence, and offering teachers with professional development programs on learner autonomy can be helpful in developing both learner and teacher autonomy.
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 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 | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".