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Record W2883800397

Virtual worlds and gamification to increase integration of international students in higher education: an inclusive design approach

2017· article· en· W2883800397 on OpenAlexvenueno aff
Bo Zhang, Nigel Robb, Joe Eyerman, Lizbeth Goodman

Bibliographic record

VenueInternational journal of e-learning & distance education · 2017
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalizationProcess (computing)MetaverseComputer scienceKnowledge managementEmpathyPedagogyVirtual realityPsychologyHuman–computer interactionBusiness
DOInot available

Abstract

fetched live from OpenAlex

In response to the growing trend of internationalisation in education, it is important to consider approaches to help international students integrate into their new settings. One possible approach involves the use of e-Learning tools, such as virtual worlds and gamification. To maximise the potential effectiveness of such tools, it may be beneficial to involve international students in a technological co-design process. This paper develops an inclusive design process based on the definitions of Inclusive Design outlined by the SMARTlab and IDRC teams, as part of a co-design specification in practice, gathering specific information about the needs of the Chinese students in Ireland at UCD through a questionnaire and an empathy-driven design approach.  From the responses of the questionnaire, we found that students would find many features that virtual environments can provide beneficial (e.g., 3D campus tours and virtual lectures). We also found that collaborative, social activities were a more popular way to potentially increase language and cultural understanding than structured courses. Finally, we learned that the incorporation of game-like elements in virtual environments requires careful planning: while this may be effective to increase user engagement with information, users do not want to have to be successful in games to gain access to essential resources or information. Based on these specific needs provided by Chinese students themselves, a virtual campus (VC) is created which based on a unique virtual platform-Terf®. Resume En reponse a la tendance croissante d’internationalisation dans l’education, il est important d’envisager des approches permettant d’aider les etudiants internationaux a integrer leurs nouveaux environnements. Une approche possible implique l’usage d’outils e-learning tels que les mondes virtuels et la ludification. Afin de maximiser l’efficacite potentielle de tels outils, il peut etre favorable d’impliquer les etudiants internationaux dans un processus de co-conception technologique. Cet article developpe un processus de conception inclusive basee sur les definitions formulees par les equipes du SMARTlab et de l’IDRC et les exigences empiriques de co-conception, definies en rassemblant des informations specifiques concernant les besoins des etudiants chinois en Irlande, a l’Universite College Dublin (UCD), par le biais d’un questionnaire et d’une approche de la conception guidee par l’empathie. Les reponses au questionnaire nous ont permis de faire ressortir que les etudiants considereraient comme benefiques plusieurs des caracteristiques envisageables des environnements virtuels (comme, par exemple, la visite du campus en 3D et les cours virtuels). Nous avons aussi vu que les activites collaboratives et sociales constitueraient un moyen plus populaire que les cours structures en vue d’accroitre potentiellement la comprehension linguistique et culturelle.  Finalement, nous avons appris que l’integration d’elements de type « jeu » dans des environnements virtuels requiert une planification soignee : tandis que cela peut etre efficace pour augmenter l’interet de l’usager pour l’information, les usagers ne veulent pas avoir a reussir aux jeux afin de pouvoir acceder aux ressources ou informations essentielles. C’est en se fondant que ces besoins specifiques enonces par les etudiants chinois eux-memes qu’un campus virtuel (CV) a ete cree sur une plateforme virtuelle appelee Terf® specialement construite a cette fin. Mots-cles : design inclusive; mondes virtuels; e-learning technologie educative; gamification; internationalisation

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.

How this classification was reachedexpand

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.038
GPT teacher head0.397
Teacher spread0.359 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2017
Admission routes1
Has abstractyes

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