Approach to M-learning Acceptance Among University Students
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
A growing number of higher education institutions have adopted tools to promote mobile learning. However, studies into the driving factors of its adoption are insufficient. This article identifies the aspects that have an effect on the adoption of mobile learning (m-learning) among university students. The theory of planned behavior (TPB) and technology acceptance model (TAM) have been shown to be valid and powerful models in the research on the adoption of learning technologies. Based on TPB and TAM, we propose a model to explain how perceptions influence m-learning adoption among Colombian university students. To confirm the acceptability of the model, a self-administered questionnaire was applied to 878 undergraduate university students from the Instituto Tecnológico Metropolitano (ITM), a higher education institution in Colombia The results suggest that all of the constructs of TPB and TAM have a moderate impact on the intention to adopt m-learning. Specifically, perceived usefulness and attitude have a significant influence on students’ acceptance of m-learning. These results can stimulate future research and promote an effective diffusion of m-learning in developing countries.
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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 | 0.005 | 0.001 |
| 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 | 0.004 | 0.003 |
| 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