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Record W4383106117 · doi:10.21556/edutec.2023.84.2769

Estado del arte sobre el uso de la realidad virtual, la realidad augmentada y el video 360° en educación superior

2023· article· es· W4383106117 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

VenueEdutec Revista Electrónica de Tecnología Educativa · 2023
Typearticle
Languagees
FieldComputer Science
TopicEducational Innovations and Technology
Canadian institutionsUniversité TÉLUQ
Fundersnot available
KeywordsHumanitiesVirtual realityPhilosophyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Las tecnologías inmersivas están cada vez más presentes en los establecimientos de educación superior. Sin embargo, creemos que es pertinente hacer un balance del impacto de estas tecnologías en la transferencia de conocimientos a los estudiantes, así como de los riesgos y limitaciones inherentes a su uso. Esta revisión de literatura basada en el método EPPI (Evidence for Policy and Practice Information and Co-ordinating) tiene como objetivo establecer el estado actual del conocimiento de las modernas tecnologías inmersivas en la educación superior. Nos centramos en la realidad virtual, la realidad aumentada y el vídeo 360°. Además, se redujo el alcance de la búsqueda seleccionando los estudios que utilizan un casco autónomo del tipo Head-Mounted Display (HMD) o gafas de realidad aumentada. El número total de artículos seleccionados para la revisión se limitó a cuarenta (40). Los resultados nos permitieron identificar los atributos y mecanismos relacionados con las aplicaciones virtuales, y describir sus ventajas y limitaciones para el aprendizaje.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
GPT teacher head0.327
Teacher spread0.314 · 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