AHCI RESEARCH GROUP

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2025

Linares-Pellicer, J.; Izquierdo-Domenech, J.; Ferri-Molla, I.; Aliaga-Torro, C.

Breaking the Bottleneck: Generative AI as the Solution for XR Content Creation in Education Book Section

In: Lecture Notes in Networks and Systems, vol. 1140, pp. 9–30, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 23673370 (ISSN).

Abstract | Links | BibTeX | Tags: Adversarial machine learning, Augmented Reality, Breakings, Content creation, Contrastive Learning, Development process, Educational context, Federated learning, Generative adversarial networks, Immersive learning, Intelligence models, Learning experiences, Mixed reality, Resource intensity, Technical skills, Virtual environments

@incollection{linares-pellicer_breaking_2025,

title = {Breaking the Bottleneck: Generative AI as the Solution for XR Content Creation in Education},

author = {J. Linares-Pellicer and J. Izquierdo-Domenech and I. Ferri-Molla and C. Aliaga-Torro},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212478399&doi=10.1007%2f978-3-031-71530-3_2&partnerID=40&md5=aefee938cd5b8a74ee811a463d7409ae},

doi = {10.1007/978-3-031-71530-3_2},

isbn = {23673370 (ISSN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lecture Notes in Networks and Systems},

volume = {1140},

pages = {9–30},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {The integration of Extended Reality (XR) technologies-Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)-promises to revolutionize education by offering immersive learning experiences. However, the complexity and resource intensity of content creation hinders the adoption of XR in educational contexts. This chapter explores Generative Artificial Intelligence (GenAI) as a solution, highlighting how GenAI models can facilitate the creation of educational XR content. GenAI enables educators to produce engaging XR experiences without needing advanced technical skills by automating aspects of the development process from ideation to deployment. Practical examples demonstrate GenAI’s current capability to generate assets and program applications, significantly lowering the barrier to creating personalized and interactive learning environments. The chapter also addresses challenges related to GenAI’s application in education, including technical limitations and ethical considerations. Ultimately, GenAI’s integration into XR content creation makes immersive educational experiences more accessible and practical, driven by only natural interactions, promising a future where technology-enhanced learning is universally attainable. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},

keywords = {Adversarial machine learning, Augmented Reality, Breakings, Content creation, Contrastive Learning, Development process, Educational context, Federated learning, Generative adversarial networks, Immersive learning, Intelligence models, Learning experiences, Mixed reality, Resource intensity, Technical skills, Virtual environments},

pubstate = {published},

tppubtype = {incollection}

}