Mapping Research on Learner Autonomy in Saudi EFL Higher Education: A Scoping Review of Empowerment and Reform Amid Vision 2030 (2016–2025)
Bibliographic record
Abstract
This study presents a scoping review of research on language learner autonomy (LLA) in Saudi EFL higher education, focusing on empirical studies published between 2016 and 2025. Guided by the PRISMA-ScR framework, the review systematically examined 28 studies selected from 218 initial records across five databases. The review examined how LLA is defined, the theoretical frameworks employed, and the methodologies utilised across 12 Saudi universities and institutions. Methodological analysis revealed 64% quantitative designs, 25% mixed-methods, and 11% qualitative approaches. The studies involved 4,847 participants, with sample sizes ranging from 25 to 630. The gender distribution consisted of 43% mixed-gender studies, 32% female-only studies, and 18% male-only studies. Geographically, 39% of studies were conducted in the Central region, 25% in the Western region. Findings reveal that 89% of studies framed LLA as learner control, while 39% showed shifts toward dynamic conceptualisations. Technology integration was observed in 68% of studies, with mobile-assisted learning in 32%. Despite Vision 2030's emphasis, only 18% of studies explicitly aligned with national reform agendas. Theoretical analysis revealed that 54% employed self-determination theory, while 36% utilised Holec's framework. Although 75% cited digital tools as enablers, pedagogical integration remained underdeveloped in 68% of cases. Notable gaps persist in gender analysis (25% of studies provide disaggregated data) and preparatory year focus (21% of studies). The review underscores the need for more theoretically grounded, methodologically robust research to advance autonomy-supportive pedagogies within Vision 2030's framework, emphasising qualitative investigations, gender-sensitive analyses, and policy alignment.
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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".