Understanding Blended Learning from Students’ Perspectives: Challenges and Opportunities in Saudi Undergraduate Settings
Bibliographic record
Abstract
This study explores Saudi EFL students’ perceptions on the implementation of blended learning (BL) at a Saudi university context. The study highlights two key aspects of BL in terms of challenges and benefits that influence BL in EFL classrooms. In other words, how do students recognize the impact of BL quality from their perspectives. Two main instruments were used: questionnaire and semi-structured interview. The data were collected from (N=32) Saudi male and female students from a Saudi university. The results of this study indicate that students show a positive attitude towards the BL approach. However, the findings reveal that students in their classrooms perceived many challenges in terms of implementing approach. Two main sources of difficulties were constantly identified: challenges initiated by students in terms of lack of technology competence to learn in BL environment and challenges initiated by the educational system in terms of teachers’ lack of suitable training. These issues were most significant in the results in relation to implementing BL in Saudi contexts.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".