MétaCan
Menu
Back to cohort
Record W1826772740 · doi:10.21432/t2k309

Un environnement 3D qui favorise le sentiment d’appartenance en situation de formation à distance

2006· article· fr· W1826772740 on OpenAlexafffundvenue
Claire IsaBelle, Nancy Vézina, Hélène Fournier

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2006
Typearticle
Languagefr
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversité de MonctonUniversity of Ottawa
FundersNational Research Council Canada
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

De plus en plus de plateformes hypermédias sont créées pour combler les besoins de la formation à distance et en ligne. Le langage de modélisation Virtual Reality Modeling Language permet de créer des représentations numériques d'un environnement 3D, imitant un monde réaliste, dans lequel l’apprenant évolue de façon interactive à l’aide d’un avatar. Une étude a été menée auprès de 40 apprenants afin de mesurer l’effet d’un environnement 3D, avec avatars, sur leur sentiment d’appartenance au groupe et sur le taux de rétention. Les apprenants qui ont suivi la formation avec le monde 3D ont affirmé avoir ressenti un sentiment d’appartenance plus élevé que ceux qui ont suivi la formation avec une plateforme de type traditionnel.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.008
GPT teacher head0.212
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Learning and TechnologySame topicVirtual Reality Applications and ImpactsFrench-language works237,207