Foreign Language Literature in the Online Mode: A Quasi-Experimental Study with College EFL Learners in Saudi Arabia
Bibliographic record
Abstract
The sudden outbreak of the Covid-19 pandemic and the subsequent drastic changes in the education sector led to a great deal of interest being generated in educational research. The corpus so added covered a wide range of issues that mushroomed in the new scenario, and as far as language research goes, there were not many areas that did not invoke new forays. However, teaching and learning of literature courses has remained a largely virgin territory and one which this study explores. Using a mixed-methods approach, this study examines the perspectives and satisfaction of EFL learners and teachers at Imam Muhammad bin Saud Islamic University (IMBSIU), Saudi Arabia, to the study of English literature in the online mode with standard online learning platforms in Imam University. This was followed by collection of quantitative data from both teachers (N= 30) and students (N= 50) using online surveys after an interventional period of six weeks during which literature lessons were delivered in a purely online mode. Data were collected via validated questionnaire supported by previous studies. Results showed that teachers reported their satisfaction due to the engagement of their students in the online literature classes. Similarly, students of the EFL literature class at IMBSIU have positive attitudes and high satisfaction on studying literature in the online mode. Furthermore, students reported gains in terms of (i) Efficacy of materials and resources; ii. Opportunities for autonomous learning; and iii. Opportunities for interaction; the teachers reported satisfaction in terms of i. Learner interaction; and ii. Professional satisfaction. The outcomes are likely to reflect on the efficacy of pedagogical practices and help enhance learning outcomes. Based on these findings, the study proposes pertinent recommendations on how online learning platforms in a tertiary setting might be utilized and enhanced over time, even when the pandemic becomes a thing of the past.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".