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Record W2170584070

Design on the MUVE: Synergizing Online Design Education with Multi-User Virtual Environments (MUVE).

2015· article· en· W2170584070 on OpenAlex
Isinsu Sakalli, Wonjoon Chung

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

Venue˜The œturkish online journal of educational technology · 2015
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceTask (project management)MultimediaThe InternetHuman–computer interactionWorld Wide WebEngineeringSystems engineering
DOInot available

Abstract

fetched live from OpenAlex

The world is becoming increasingly virtual. Since the invention of the World Wide Web, information and human interaction has been transferring to the web at a rapid rate. Education is one of the many institutions that is taking advantage of accessing large numbers of people globally through computers. While this can be a simpler task for disciplines focusing on lecture-based learning, it has been a challenge for the field of design. Transferring its studio-based education structure, where students draw, build, collaborate, test and iterate their work, requires using technologies outside of the common ones in information-based disciplines. This literature review analyses the current tools used in online design education and an alternative technology, called multi-user virtual environments (MUVE). Addressing MUVE's technological features, limitations and use in education, this paper proposes that a synergy between MUVE and online design education would be mutually beneficial.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.058
GPT teacher head0.311
Teacher spread0.253 · 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