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Record W4317597600 · doi:10.5539/hes.v13n1p35

The Virtual Interactive Learning Model using Imagineering Process via Metaverse

2023· article· en· W4317597600 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHigher Education Studies · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsMetaverseInstructional simulationComputer scienceProcess (computing)Human–computer interactionInstructional designEducational technologyActive learning (machine learning)Virtual learning environmentVirtual realityMultimediaArtificial intelligenceMathematics educationPsychology

Abstract

fetched live from OpenAlex

The virtual interactive learning model using imagineering process as a tool to promote happy learning for digital age learners. The concept is based on the combination of virtual learning environment and metaverse in order to create learning experience via virtual community. The objectives of this research are (1) to study and synthesise the conceptual framework of the virtual interactive learning model using imagineering process via metaverse, (2) to develop the virtual interactive learning model using imagineering process via metaverse, and (3) to study the results after using the virtual interactive learning model using imagineering process via metaverse. The participants in this research include seven experts from various institutions, all of whom are specialised in the design and development of instruction models and instruction systems. The research tools consist of (1) the virtual interactive learning model using imagineering process via metaverse, and (2) the evaluation form on the suitability of the virtual interactive learning model using imagineering process via metaverse. The results, which are in consistence with the expectation of the researchers, show that (1) this research can be used as a guideline to develop the virtual interactive learning system using imagineering process via metaverse, which can promote happy learning, and it consists of six steps of imagineering process integrated with learning through virtual environments via metaverse; thereby, users can interact in the virtual world and exchange knowledge with one other through virtual reality technology, (2) the overall suitability of the development of the virtual interactive learning model using imagineering process via metaverse (overall elements) is at the very high level, and (3) the overall suitability of the development of the virtual interactive learning model using imagineering process via metaverse is at the very high level.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.080
GPT teacher head0.411
Teacher spread0.331 · 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