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Record W4388785139 · doi:10.5539/hes.v13n4p193

The Project-based Learning: PjBL via Brainstorming with Metaverse to Promote Multimedia Production Skills

2023· article· en· W4388785139 on OpenAlexvenueno aff
Phanuwat Kongkhen, Pinanta Chatwattana

Bibliographic record

VenueHigher Education Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
FundersKing Mongkut's University of Technology North Bangkok
KeywordsBrainstormingMetaverseComputer scienceProject-based learningProcess (computing)Knowledge managementMathematics educationPsychologyVirtual realityHuman–computer interactionArtificial intelligence

Abstract

fetched live from OpenAlex

The design of the project-based learning, or PjBL, via brainstorming with metaverse to promote multimedia production skills is based on the integration of the concepts of project-based learning processes via brainstorming with virtual world technologies for use in the instruction management. Thereby, the instruction management in this way is said to develop learners’ multimedia production skills as it encourages them to search for knowledge on their own, which shall also enable them to increase knowledge from practices and enhance necessary skills for the 21st century learners. The objectives of this research are (1) to study and synthesize the learning process the PjBL via brainstorming with metaverse, (2) to design the PjBL via brainstorming model with metaverse, and (3) to study the results of the design of the PjBL via brainstorming model with metaverse. The results of this research show that (1) the overall suitability of the design of the PjBL via brainstorming model with metaverse is at highest level (Mean = 4.62, SD. = 0.47), and (2) the overall suitability of the elements of the PjBL via brainstorming model with metaverse is at highest level (Mean = 4.75, SD. = 0.36).

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 categoriesScience 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 score0.273
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.399
Teacher spread0.352 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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