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Record W4401125752 · doi:10.54337/nlc.v13.8553

Tipping the canoe: What can be learned from a postdigital analysis of augmented and virtual reality in networked learning?

2024· article· en· W4401125752 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

VenueProceedings of the International Conference on Networked Learning · 2024
Typearticle
Languageen
FieldComputer Science
TopicDigital Education and Society
Canadian institutionsSaskatchewan PolytechnicUniversity of Saskatchewan
Fundersnot available
KeywordsAugmented realityVignetteNoticeComputer scienceVirtual realityContext (archaeology)ContextualizationPerspective (graphical)MultimediaHuman–computer interactionValue (mathematics)MirroringPsychologyArtificial intelligenceSocial psychology

Abstract

fetched live from OpenAlex

In this paper, the authors use a postdigital lens to examine augmented (AR) and virtual reality (VR) as potentially effective tools for networked learning. The postdigital perspective suggests that the ‘digital’ is so pervasive that it is no longer considered novel or noteworthy; rather, it is so embedded in our day-to-day lives that it now evades notice. This examination draws upon the concepts of analogue and digital to explore ontological and epistemological characteristics of AR and VR as well as how media and materials may shift on a continuum or manifest both characteristics concurrently. Two vignettes are used to create a shared context and atmosphere from which to consider the pedagogical use of these technologies. One vignette describes a VR app that invites the learners into a canoe where they are immersed into a lesson about Indigenous constellations; the second describes an AR app in which the learners direct their smartphones up at the sky also to learn about constellations. While the learning goals are similar, the experiences are differently nuanced. The paper offers a discussion of considerations that may be useful in designing learning experiences with these technologies. The authors discuss the analogue and digital characteristics as well as the freedoms and constraints relative to sites of learning, activities, learner configurations, and representations of learning. A postdigital analysis benefits from ‘shifting work’; that is, much can be learned from shifting between analogue and digital. Such shifting may surface failures, depletion of resources, and the emergence of new entities. The value of examining the digital, analogue, ontology, and epistemology of AR and VR is that it helps to make the human-technology relationship more perceptible. In becoming more aware of the taken-for-granted aspects of learning technologies, it is possible to more effectively design for learning.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.292
Teacher spread0.248 · 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