A Preliminary Study On Mobile Learning Readiness Among Undergraduates Of Universiti Malaysia Sabah, Sabah, Malaysia
Bibliographic record
Abstract
Universiti Malaysia Sabah (UMS) is actively involved in e-learning since 2002. The university’s moodle platform is used for e-learning by the majority of the undergraduates taking various courses. Of lately, there seems to be an indication of increase ownership of smart phones capable of mobile learning (m-learning) by undergraduates of UMS. This study is conducted at the second quarter of 2012 to investigate, among others, the extent of the usage of mobile phone and the perceptions of the students on their readiness to embark on m-learning. The 477 respondents were from 5 science and non-science faculties in the university. The findings indicate that 190 (39.8 percent) and 48 (10.1 percent) respondents respectively have a smart phone and a computer tablet (or pad). The study also shows that 87.0 percent of the respondents agree that learning through mobile devices gives them more flexibility. The findings indicate that the level of readiness for m-learning in UMS is at moderate level. Many of the respondents prefer to use m-learning in accessing course notes (57.9 percent), engaging in learning activity (73.8 percent), getting information from internet (91.0 percent) and learning collaboration with their peers via social networks such as Facebook (82.0 percent). This paper highlights the findings and implications to the upcoming m-learning project at the university.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".