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Record W4400229969 · doi:10.1109/mcg.2024.3419699

Extended Realities for Sensorially Diverse Children

2024· article· en· W4400229969 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.

Bibliographic record

VenueIEEE Computer Graphics and Applications · 2024
Typearticle
Languageen
FieldPsychology
TopicChild Therapy and Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsComputer scienceComputer graphics (images)Multimedia

Abstract

fetched live from OpenAlex

Learning space for children with different sensory needs, nowadays, can be interactive, multisensory experiences, designed collaboratively by 1) specialists in special-needs learning, 2) extended realities (XR) technologists, and 3) sensorial diverse children, to provide the motivation, challenge, and development of key skills. While traditional audio and visual sensors in XR are challenging for XR applications to meet the needs of visually and hearing impaired sensorial-diverse children, our research goes a step ahead by integrating sensory technologies including haptic, tactile, kinaesthetic, and olfactory feedback that was well received by the children. Our research also demonstrates the protocols for 1) development of a suite of XR-applications; 2) methods for experiments and evaluation; and 3) tangible improvements in XR learning experience. Our research considered and is in compliance with the ethical and social implications and has the necessary approval for accessibility, user safety, and privacy.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.305
Teacher spread0.283 · 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