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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®. RésuméEn réponse à la tendance croissante d’internationalisation dans l’éducation, il est important d’envisager des approches permettant d’aider les étudiants internationaux à intégrer 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’efficacité potentielle de tels outils, il peut être favorable d’impliquer les étudiants internationaux dans un processus de co-conception technologique. Cet article développe un processus de conception inclusive basée sur les définitions formulées par les équipes du SMARTlab et de l’IDRC et les exigences empiriques de co-conception, définies en rassemblant des informations spécifiques concernant les besoins des étudiants chinois en Irlande, à l’Université Collège Dublin (UCD), par le biais d’un questionnaire et d’une approche de la conception guidée par l’empathie. Les réponses au questionnaire nous ont permis de faire ressortir que les étudiants considèreraient comme bénéfiques plusieurs des caractéristiques envisageables des environnements virtuels (comme, par exemple, la visite du campus en 3D et les cours virtuels). Nous avons aussi vu que les activités collaboratives et sociales constitueraient un moyen plus populaire que les cours structurés en vue d’accroitre potentiellement la compréhension linguistique et culturelle. Finalement, nous avons appris que l’intégration d’éléments de type « jeu » dans des environnements virtuels requiert une planification soignée : tandis que cela peut être efficace pour augmenter l’intérêt de l’usager pour l’information, les usagers ne veulent pas avoir à réussir aux jeux afin de pouvoir accéder aux ressources ou informations essentielles. C’est en se fondant que ces besoins spécifiques énoncés par les étudiants chinois eux-mêmes qu’un campus virtuel (CV) a été créé sur une plateforme virtuelle appelée Terf® spécialement construite à cette fin. Mots-clés: 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations19
Published2017
Admission routes1
Has abstractyes

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