Project-based Learning with Demonstration through the Metaverse to Promote Media Production Skills and Multimedia Innovations
Bibliographic record
Abstract
This research employed a Research and Development (R&D) approach to investigate the integration of Project-based Learning (PBL) with Demonstration through the Metaverse to promote Media Production Skills and Multimedia Innovation. The study's objectives were to synthesize, design, develop, and evaluate this integrated learning system. Expert evaluations confirmed the high suitability of the overall design (Mean = 4.77, S.D. = 0.43) and its components at the highest level. Similarly, the quality of the developed learning system was assessed as being at the highest level (Overall Mean = 4.70, S.D. = 0.37). Furthermore, student assessment results were at a very good level, showing an average score of (84.50 percent) for media production skills and (85.80 percent) for multimedia innovations. These findings affirm that the integrated PBL system with demonstration through the Metaverse provides a highly suitable and effective guideline for developing learning to enhance media creation skills and multimedia innovation in learners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".