Attitudes and Usage of MALL Among Saudi University EFL Students
Bibliographic record
Abstract
Possessing distinctive features of mobility, portability, and connectivity, mobile technology has inevitably become an integrated part of everyday instructional practices and activities. Foreign language learning, especially English language, could gain substantial benefits from these advances in technology to enhance learning experiences and respond to learners’ various needs and interests. There is a far-reaching investment in mobile learning projects at many Saudi Arabian universities including King Abdul Aziz University and Imam Mohammad Ibn Saud Islamic University. Moreover, the Ministry of Higher Education has a long-term plan known as “The Afaq Project” which is examining the current and future challenges for implementing online learning in all universities. Hence, the current study aims to examine students’ attitudes towards and their usage of smart phones when learning English as a foreign language. A questionnaire was designed and distributed among first year university students at the Northern Border University in Saudi Arabia. It included 25 items, each with varies in responses. A systematic sampling approach was adopted to choose the participants for this study.The duration of administering the questionnaire was from November 2017 to December 2017 and it was applied to 205 students.The Statistical Package for the Social Sciences (SPSS) program was used for data analysis of the questionnaire responses.The final data were used to test the hypothesis of the research using the Chi-Squared method applied to a frequency table.Results revealed that students have positive attitudes towards using mobiles phones and that they were very interested in learning English by using technology.
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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 | 0.000 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".