Mobile learning frameworks and pedagogy: A systematic review
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
Abstract This article provides a systematic review of mobile learning frameworks that address issues of pedagogy published between 2011 and 2022. The objective of the review was to gain a clear picture of recent developments in mobile learning frameworks to provide an understanding of current directions in mobile learning pedagogy. Eighteen peer‐reviewed journal articles that presented new mobile learning pedagogical frameworks were examined and evaluated based on the characteristics of each framework. The two main areas of analysis were the pedagogical approaches integrated into the frameworks and their definitions of mobile learning. We conclude that mobile learning frameworks have become more diverse over time, in many cases tending to focus on specific aspects of mobile learning rather than attempting to address overarching concepts. With respect to pedagogies and their underlying theories of learning, social constructivism, heutagogy, collaborative learning, experiential learning, inquiry‐based learning, and student‐centred learning were mentioned most frequently. However, although many frameworks make reference to pedagogy, there is limited analysis of how mobile learning pedagogy might be defined as distinct from other contexts of learning. The key characteristics of mobile learning, consistent through most of the reviewed frameworks, comprise the portability of mobile devices across multiple contexts, connectivity, and accessibility, as well as learner‐centredness (including personalisation and self‐regulation). One key aspect of identifying the uniqueness and future potential of mobile learning is the special affordances addressed by mobile learning theory. We conclude that this is an area where further research is required.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 |
| 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