Undergraduate EFL Learners’ Use and Acceptance of Mobile-Assisted Language Learning: A Structural Equation Modeling Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mobile-assisted language learning has received growing attention from the technology industry through the proliferation of mobile learning platforms and applications. The literature has promoted the potential effectiveness of such platforms. However, little attention has been given to learners’ use behavior and perceptions, which play an essential role in successful implementation. In addition, research is scare on the acceptance and use of MALL to learn English in Middle Eastern countries. The Unified Theory of Acceptance and Use of Technology 2 was employed in this study to examine the main factors affecting the acceptance and use of MALL among 945 undergraduate EFL learners in Saudi Arabia. The findings demonstrated that the constructs of habit, performance expectancy, facilitating conditions, hedonic motivation, and social influence were significant indicators of EFL learners’ behavioral intention to use MALL. Out of habit, behavioral intention, and facilitating conditions, habit was the only construct with a significant impact on participants’ use behavior.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 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 it