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Natural Language Processing for a Personalised Educational Experience in Virtual Reality

Alghamdi, Nuha; Cristea, Alexandra I.

Authors

Nuha Alghamdi nuha.s.alghamdi@durham.ac.uk
PGR Student Doctor of Philosophy



Contributors

Andrew M. Olney
Editor

Irene-Angelica Chounta
Editor

Zitao Liu
Editor

Olga C. Santos
Editor

Ig Ibert Bittencourt
Editor

Abstract

Virtual Reality (VR) is a technology that creates a simulated immersive environment, allowing users to be more engaged and interactive. The user can interact with a VR environment using head-mounted displays, hand controllers, and, in some cases, speech. VR has been widely used in various industries and areas, one of which is education, to build simulated and interactive experiences. However, little prior research has explored the integration of speech input in VR educational environments. Moreover, there is currently a lack of understanding of how speech and verbal/textual interaction can support personalisation in VR in general, and in the educational domain, in particular. Thus, this research targets to fill this gap. Our long-term goal is to incorporate speech and text-based interaction in the VR learning environment, to support smooth and natural personalisation of the learning interaction. Personalisation here is used in the classical AI in Education sense, of adapting the learning system to a learner, e.g. to their level or needs. As a first step, we have started exploring and comparing different speech recognition models that support VR applications. Further, we will personalise the user experience, by utilising the text generated from the speech input and applying NLP and adaptation techniques to it. Furthermore, we will investigate the impact of this kind of personalisation on learner engagement and outcomes.

Citation

Alghamdi, N., & Cristea, A. I. (2024, July). Natural Language Processing for a Personalised Educational Experience in Virtual Reality. Presented at Artificial Intelligence in Education (AIED 2024), Recife, Brazil

Presentation Conference Type Conference Paper (published)
Conference Name Artificial Intelligence in Education (AIED 2024)
Start Date Jul 8, 2024
End Date Jul 12, 2024
Acceptance Date May 31, 2024
Online Publication Date Jul 2, 2024
Publication Date 2024
Deposit Date Oct 16, 2024
Print ISSN 0302-9743
Publisher Springer
Peer Reviewed Peer Reviewed
Pages 355-361
Series Title Communications in Computer and Information Science
Book Title Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky
ISBN 9783031643118
DOI https://doi.org/10.1007/978-3-031-64312-5_43
Public URL https://durham-repository.worktribe.com/output/2960781