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Record W4415307051 · doi:10.5539/hes.v15n4p367

Project-based Learning with Demonstration through the Metaverse to Promote Media Production Skills and Multimedia Innovations

2025· article· W4415307051 on OpenAlexvenueno aff
Phanuwat Kongkhen, Kanitta Hinon, Panita Wannapiroon

Bibliographic record

VenueHigher Education Studies · 2025
Typearticle
Language
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
FundersKing Mongkut's University of Technology North Bangkok
KeywordsMetaverseProduction (economics)Quality (philosophy)Instructional designEducational technologyTeaching methodInteractive mediaActive learning (machine learning)

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.372
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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