An Empirical Study of Critical Success Factors of Mobile Learning Platform from the Perspective of Instructors
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 learning is newest learning platform and based on the rapid rate of proliferation of mobile technology throughout the world is expected to grow at a rapid rate. However, the adoption of m-Learning is proceeding at a cautious rate. This mismatch in the rate of growth of the technology itself and the use of the technology in learning is a subject of extensive interest to researchers. However, research in the area has been mostly focused on understanding the success factors of the platform from learners’ perspective. In this research, we have conducted an extensive analysis of the extent to which various factors are considered to impact the success of mobile learning from the perspective of instructors. This is because instructors not only are one of the core users of the platform they also hold a great deal of influence in promoting the platform usage among learners. The results of the research were not found to be statistically significant showing that greater population size is required to assess various hypotheses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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 it