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Record W1982583407 · doi:10.1108/17415651111141821

Virtual simulations and serious games in a laptop‐based university

2011· article· en· W1982583407 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInteractive Technology and Smart Education · 2011
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsSickKids FoundationThe Wilson CentreHospital for Sick ChildrenUniversity of TorontoOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ontario Institute of Technology
KeywordsLaptopComputer scienceExperiential learningPerceptionMultimediaEducational technologyMathematics educationInstructional simulationWork (physics)Teaching methodTechnology integrationHuman–computer interactionPsychology

Abstract

fetched live from OpenAlex

Purpose – Gaming and interactive virtual simulation environments support a learner‐centered educational model allowing learners to work through problems acquiring knowledge through an active, experiential learning approach. To develop effective virtual simulations and serious games, the views and perceptions of learners and educators must be assessed and taken into account, regarding their use in the classroom. This paper aims to present the results of two surveys conducted to assess faculty and student perceptions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.017
GPT teacher head0.297
Teacher spread0.280 · 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