Leveraging Virtual Reality and Machine Learning as Mediated Learning Tools for Social Skill Development in Learners with Autism Spectrum Condition

Hughes-Roberts, Thomas and Cui, Vanessa and Mahmud, Mufti and Brown, David (2022) Leveraging Virtual Reality and Machine Learning as Mediated Learning Tools for Social Skill Development in Learners with Autism Spectrum Condition. In: Universal Access in Human-Computer Interaction. User and Context Diversity. Springer. ISBN 9783031050381

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Abstract

Learners with Autism Spectrum Condition (ASC) are often characterized as having deficits in core social competencies affecting ability to communicate and interact with other people across multiple contexts. However, such defi-cit views of ASC lead to narrow interventions that cannot be generalized to wider learning contexts nor the real world. Taking a non-deficit view can of-fer a means of broadening understanding of ASC by taking a more holistic view of an individual. Thoughtfully designed VR solutions that take a non-deficit view can provide learning tools allow learners to develop their self-determination awareness and skills such as decision-making, self-advocacy, reflective problem-solving. Furthermore, through the use of machine learn-ing approaches such solutions have the potential to provide real-time moni-toring of learners during interaction offering a holistic understanding of in-dividuals with ASC. This position paper sets out the support case for utiliz-ing VR through non-deficit models and examines the role machine learning can play in further understanding of learners with ASC. It is intended that this sets out a case for future research directions.

Item Type: Book Section
Dates:
DateEvent
23 May 2022Published
Subjects: CAH22 - education and teaching > CAH22-01 - education and teaching > CAH22-01-01 - education
Divisions: Faculty of Health, Education and Life Sciences > Centre for Study of Practice and Culture in Education (C-SPACE)
Depositing User: Vanessa Cui
Date Deposited: 03 May 2022 13:36
Last Modified: 23 May 2024 03:00
URI: https://www.open-access.bcu.ac.uk/id/eprint/13199

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