Publications

@inproceedings{li_spatialearn_2025,

title = {SpatiaLearn: Exploring XR Learning Environments for Reflective Writing},

author = {J. Li and S. P. Neshaei and L. Müller and R. Rietsche and R. L. Davis and T. Wambsganss},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005757843&doi=10.1145%2f3706599.3719742&partnerID=40&md5=6e9ce83d3508cb377e209edd6884c505},

doi = {10.1145/3706599.3719742},

isbn = {979-840071395-8 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Conf Hum Fact Comput Syst Proc},

publisher = {Association for Computing Machinery},

abstract = {Reflective writing promotes deeper learning by enhancing metacognitive awareness and critical thinking, but learners often struggle with structuring their reflections and maintaining focus. Generative AI and advances in spatial computing offer promising solutions. Extended reality (XR) environments create immersive, distraction-free settings, while conversational agents use dialog-based scaffolding guides to structure learners’ thoughts. However, research on combining dialog-based scaffolding with XR for reflective writing remains limited. To address this, we introduce SpatiaLearn, an adaptive XR tool that enhances reflective writing through conversational guidance in both traditional and immersive environments. A within-subjects study (N = 19) compared participants’ performance in traditional laptop and XR environments. Qualitative analysis shows the spatial interface enhances engagement but raises challenges like unfamiliar interactions and health concerns, requiring task adaptation for XR. This study advances the design of immersive tools for reflective writing, highlighting both the opportunities and challenges of spatial interfaces. © 2025 Copyright held by the owner/author(s).},

keywords = {Adaptive Education, Conversational Agents, Conversational Tutoring, Critical thinking, Extended reality (XR), Immersive, Learning Environments, Metacognitive awareness, Reflective writing, Spatial computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{krauss_opportunities_2024,

title = {Opportunities and Challenges in Developing Educational AI-Assistants for the Metaverse},

author = {C. Krauss and L. Bassbouss and M. Upravitelev and T. -S. An and D. Altun and L. Reray and E. Balitzki and T. El Tamimi and M. Karagülle},

editor = {Sottilare R.A. and Schwarz J.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196214138&doi=10.1007%2f978-3-031-60609-0_16&partnerID=40&md5=9a66876cb30e9e5d287a86e6cfa66e05},

doi = {10.1007/978-3-031-60609-0_16},

isbn = {03029743 (ISSN); 978-303160608-3 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {14727 LNCS},

pages = {219–238},

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

abstract = {The paper explores the opportunities and challenges for metaverse learning environments with AI-Assistants based on Large Language Models. A proof of concept based on popular but proprietary technologies is presented that enables a natural language exchange between the user and an AI-based medical expert in a highly immersive environment based on the Unreal Engine. The answers generated by ChatGPT are not only played back lip-synchronously, but also visualized in the VR environment using a 3D model of a skeleton. Usability and user experience play a particularly important role in the development of the highly immersive AI-Assistant. The proof of concept serves to illustrate the opportunities and challenges that lie in the merging of large language models, metaverse applications and educational ecosystems, which are self-contained research areas. Development strategies, tools and interoperability standards will be presented to facilitate future developments in this triangle of tension. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},

keywords = {3D modeling, AI-assistant, AI-Assistants, Computational Linguistics, Computer aided instruction, Concept-based, E-Learning, Education, Interoperability, Language Model, Large language model, large language models, Learning Environments, Learning systems, Learning Technologies, Learning technology, LLM, Metaverse, Metaverses, Natural language processing systems, Proof of concept, User interfaces, Virtual assistants, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{velev_challenges_2024,

title = {Challenges of Merging Generative AI with Metaverse for Next-Gen Education},

author = {D. Velev and L. Steshina and I. Petukhov and P. Zlateva},

editor = {Tallon-Ballesteros A.J.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215823646&doi=10.3233%2fFAIA241462&partnerID=40&md5=a3ed4e8486e2e32d0856a71a3a87496c},

doi = {10.3233/FAIA241462},

isbn = {09226389 (ISSN); 978-164368569-4 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Front. Artif. Intell. Appl.},

volume = {398},

pages = {606–616},

publisher = {IOS Press BV},

abstract = {The integration of Generative Artificial Intelligence (GenAI) with the Metaverse for a next-generation education is a complex but challenging task. The GenAI-enhanced Metaverse classrooms require innovative instructional designs that use virtual reality and augmented reality to enhance engagement and personalized learning. Educators must adapt to new roles over traditional teaching methods, while learners need to develop digital literacy skills that are essential for navigating and inhabiting in these environments. Such learning environments require significant advancements in real-time processing, scalability and interoperability of different platforms, while ensuring data privacy and security. The equity of access to high-speed internet and advanced devices still remains a serious barrier, which can increase the potential existing inequalities between different educational environments. Ethical considerations, including the responsible use of GenAI, the creation of unbiased educational content, and the psychological impacts of extended usage of virtual reality, are also of important consideration. The aim of the paper is to explore in detail the different challenges through a comprehensive analysis of the obstacles and potential solutions and to propose a collaborative framework involving educators, technologists, policymakers and industry stakeholders to address the effective implementation of the integration of GenAI and the Metaverse for a next generation education. © 2024 The Authors.},

keywords = {Adversarial machine learning, Augmented Reality, Contrastive Learning, Data privacy and securities, Digital literacies, Education, Federated learning, Generative adversarial networks, Generative AI, High speed internet, Instructional designs, Learning Environments, Metaverse, Metaverses, Personalized learning, Realtime processing, Teaching methods, Virtual environments, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{augelloPersonalIntelligentCoach2016,

title = {A Personal Intelligent Coach for Smart Embodied Learning Environments},

author = { Agnese Augello and Ignazio Infantino and Adriano Manfre and Giovanni Pilato and Filippo Vella and Manuel Gentile and Giuseppe Citta and Giulia Crifaci and Rossella Raso and Mario Allegra},

editor = { Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},

doi = {10.1007/978-3-319-39345-2_56},

isbn = {978-3-319-39345-2 978-3-319-39344-5},

year  = {2016},

date = {2016-01-01},

booktitle = {Intelligent Interactive Multimedia Systems and Services 2016},

volume = {55},

pages = {629--636},

publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},

address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},

series = {Smart Innovation, Systems and Technologies},

abstract = {Within a Smart Learning Environment (SLE) learners are involved in a new learning process tailored to create a continuum of education by extending the current educational formal settings to real-life informal learning context. The goal of this paper is to describe the Cognitive Architecture (CA) of a Personal Intelligent Coach able tomanage learning tasks and interactions within a complex Smart Learning Environment (SLE). PICo has two possible embodiments: humanoid robot, and an avatar on mobile device. We argue that the proposed intelligent coach can adapt to the contents, to the students needs and can evolve its strategies according the learning process.},

keywords = {Cognitive Architectures, Education, Embodied Cognition, Humanoid Robots, Learning Environments, Social Robots},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{augello_personal_2016,

title = {A Personal Intelligent Coach for Smart Embodied Learning Environments},

author = {Agnese Augello and Ignazio Infantino and Adriano Manfre and Giovanni Pilato and Filippo Vella and Manuel Gentile and Giuseppe Citta and Giulia Crifaci and Rossella Raso and Mario Allegra},

editor = {Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},

doi = {10.1007/978-3-319-39345-2_56},

isbn = {978-3-319-39345-2 978-3-319-39344-5},

year  = {2016},

date = {2016-01-01},

booktitle = {Intelligent Interactive Multimedia Systems and Services 2016},

volume = {55},

pages = {629–636},

publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},

address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},

series = {Smart Innovation, Systems and Technologies},

abstract = {Within a Smart Learning Environment (SLE) learners are involved in a new learning process tailored to create a continuum of education by extending the current educational formal settings to real-life informal learning context. The goal of this paper is to describe the Cognitive Architecture (CA) of a Personal Intelligent Coach able tomanage learning tasks and interactions within a complex Smart Learning Environment (SLE). PICo has two possible embodiments: humanoid robot, and an avatar on mobile device. We argue that the proposed intelligent coach can adapt to the contents, to the students needs and can evolve its strategies according the learning process.},

keywords = {Cognitive Architectures, Education, Embodied Cognition, Humanoid Robots, Learning Environments, Social Robots},

pubstate = {published},

tppubtype = {inproceedings}

}