Innovative Arts-Based Learning Approaches adapted for Mobile Learning
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
Online learning continues to evolve from computer-based learning to more focus on mobile learning. With this evolution comes the need to develop (and evaluate) instructional strategies effective in mobile learning. This work-in-progress features a description of four innovative instructional strategies adapted from approaches we developed, used, and evaluated successfully in computer-based online learning. These newly adapted strategies –poetweet, photo pairing, reflective mosaic, and the six-word story– all use arts-based approaches. In our past research we found similar strategies developed for online teaching encouraged interaction, enhanced social presence, and facilitated community. This paper features a description of these modified learning activities recreated for the mobile learning environment. We have completed preliminary testing of these newly revised learning activities in m-learning, and in the future we will formally study these to determine if arts-based strategies revised to suit m-learning create the same positive outcomes as were found when we used arts-based approaches in e-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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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