Synthesis of Framework of Virtual Immersive Learning Environments (VILEs) Based on Digital Storytelling to Enhance Deeper Learning for Undergraduate Students
Bibliographic record
Abstract
This study aimed to synthesize theoretical and designing framework of Virtual Immersive Learning Environments (VILEs) based on digital storytelling to enhance deeper learning for undergraduate students. Documents analysis and survey research were employed in this study. The procedures were as follows: (1) to examine and analyze the principles, theories and related researches, (2) to study instructional context, (3) to synthesize the theoretical framework, and (4) to synthesize the designing framework. The results revealed that the theoretical framework comprised of four bases was as follows: (1) immersive technology, (2) digital storytelling, (3) Stories evaluation and (4) deeper learning. The designing framework consisted of 4 elements, were as follows: (1) VILEs based on digital storytelling to enhance deeper learning, (2) Supporting Cognitive, (3) Supporting Interpersonal and (4) Support Intrapersonal.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".