A Review on the Use and Perceived Effects of Mobile Blogs on Learning in Higher Educational Settings
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 technology is affecting the way we learn and teach in higher education. An interesting mobile tool for supporting learning and instruction is by using mobile blogs or “moblogs”. This review focuses on existing studies implementing moblogs for learning purposes in higher educational settings. A total of 16 studies were selected for the review. The constant-comparative method was used to analyze the studies. Results from the data analysis indicate that the findings fall into two overarching groups, which are: (i) usage of moblogs; and (ii) perceived effects of moblogs. Seven categories for moblog usage were identified, namely: (i) moblogs were used for context-sensitive learning; (ii) for collaboration in groups; (iii) as a tool for interaction and communication for learning; (iv) as personal learning diaries; (v) to facilitate learning at students’ own time and pace; (vi) as a tool for feedback on instruction; and (vii) for reflections in learning. Meanwhile, three categories were discovered for perceived effects of moblogs, which are: (i) perceived affective effects in terms of satisfaction and attitude; (ii) perceived social effects on students; and (iii) negative perception of moblog in terms of personal and technical factors. These categories are discussed as factors that could promote the use of moblogs for learning in higher education. Directions for future research are also discussed according to these categories as a basis for future work on moblogs for learning.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it