WhatsApp as a Supporter Tool in Language Learning: A Study of Saudi EFL Learners’ Perceptions
Bibliographic record
Abstract
Technology has literally become inseparable from modern day living as it always stays with us in all places and times. Therefore, prudence demands that teachers too, make positive use of it for language learning/teaching. This study compares the impact of WhatsApp based learning activities (WBLA) with conventional activities on boosting the four language skills of Saudi EFL students. The study also investigates Saudi EFL students' perceptions on using WBLA as a tool of English language learning, motivation and autonomy. A close-ended questionnaire was developed to collect data from 100 Saudi EFL undergraduate students at Duba, University of Tabuk, the subjects of this study. The investigation showed that WBLA has a positive impact on shaping the Saudi EFL undergraduates’ perceptions to language learning. Moreover, results indicate that male learners outperformed females in all the four skills. The study, therefore, concludes that WBLA should be integrated in all EFL classes. This study establishes that novel use of technology offers effective assistance in the language 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 | 0.004 |
| 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 | 0.000 | 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".