Enhancing motivation in online courses with mobile communication tool support: A comparative study
Bibliographic record
Abstract
Mobile technologies have helped establish new channels of communication among learners and instructors, potentially providing greater access to course information, and promoting easier access to course activities and learner motivation in online learning environments. The paper compares motivation between groups of learners being taught through an online course based on an e-learning system with and without the support of mobile communication tools, respectively. These tools, which are implemented on a mobile phone, extend the use of the existing Moodle learning management system (LMS) under the guidance of a mobile communication tools framework. This framework is considered to be effective in promoting learner motivation and encouraging interaction between learners and instructors as well as among learner peers in online learning environments. A quasi-experimental research design was used to empirically investigate the influence of these tools on learner motivation using subjective assessment (for attention, relevance, confidence, satisfaction, and social ability) and objective assessment (for disengagement, engagement, and academic performance). The results indicate that the use of the tools was effective in improving learner motivation, especially in terms of the attention and engagement variables. Overall, there were statistically significant differences in subjective motivation, with a higher level achieved by experimental-group learners (supported by the tools) than control-group learners (unsupported by the tools).
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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 | 0.005 | 0.002 |
| 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 | 0.000 |
| Open science | 0.001 | 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 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".