AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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Here you can find the complete list of our publications.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Barbu, M.; Iordache, D. -D.; Petre, I.; Barbu, D. -C.; Băjenaru, L.
Framework Design for Reinforcing the Potential of XR Technologies in Transforming Inclusive Education Journal Article
In: Applied Sciences (Switzerland), vol. 15, no. 3, 2025, ISSN: 20763417 (ISSN).
Abstract | Links | BibTeX | Tags: Adaptive Learning, Adversarial machine learning, Artificial intelligence technologies, Augmented Reality, Contrastive Learning, Educational Technology, Extended reality (XR), Federated learning, Framework designs, Generative adversarial networks, Immersive, immersive experience, Immersive learning, Inclusive education, Learning platform, Special education needs
@article{barbu_framework_2025,
title = {Framework Design for Reinforcing the Potential of XR Technologies in Transforming Inclusive Education},
author = {M. Barbu and D. -D. Iordache and I. Petre and D. -C. Barbu and L. Băjenaru},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217742383&doi=10.3390%2fapp15031484&partnerID=40&md5=3148ff2a8a8fa1bef8094199cd6d32e3},
doi = {10.3390/app15031484},
issn = {20763417 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Applied Sciences (Switzerland)},
volume = {15},
number = {3},
abstract = {This study presents a novel approach to inclusive education by integrating augmented reality (XR) and generative artificial intelligence (AI) technologies into an immersive and adaptive learning platform designed for students with special educational needs. Building upon existing solutions, the approach uniquely combines XR and generative AI to facilitate personalized, accessible, and interactive learning experiences tailored to individual requirements. The framework incorporates an intuitive Unity XR-based interface alongside a generative AI module to enable near real-time customization of content and interactions. Additionally, the study examines related generative AI initiatives that promote inclusion through enhanced communication tools, educational support, and customizable assistive technologies. The motivation for this study arises from the pressing need to address the limitations of traditional educational methods, which often fail to meet the diverse needs of learners with special educational requirements. The integration of XR and generative AI offers transformative potential by creating adaptive, immersive, and inclusive learning environments. This approach ensures real-time adaptability to individual progress and accessibility, addressing critical barriers such as static content and lack of inclusivity in existing systems. The research outlines a pathway toward more inclusive and equitable education, significantly enhancing opportunities for learners with diverse needs and contributing to broader social integration and equity in education. © 2025 by the authors.},
keywords = {Adaptive Learning, Adversarial machine learning, Artificial intelligence technologies, Augmented Reality, Contrastive Learning, Educational Technology, Extended reality (XR), Federated learning, Framework designs, Generative adversarial networks, Immersive, immersive experience, Immersive learning, Inclusive education, Learning platform, Special education needs},
pubstate = {published},
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This study presents a novel approach to inclusive education by integrating augmented reality (XR) and generative artificial intelligence (AI) technologies into an immersive and adaptive learning platform designed for students with special educational needs. Building upon existing solutions, the approach uniquely combines XR and generative AI to facilitate personalized, accessible, and interactive learning experiences tailored to individual requirements. The framework incorporates an intuitive Unity XR-based interface alongside a generative AI module to enable near real-time customization of content and interactions. Additionally, the study examines related generative AI initiatives that promote inclusion through enhanced communication tools, educational support, and customizable assistive technologies. The motivation for this study arises from the pressing need to address the limitations of traditional educational methods, which often fail to meet the diverse needs of learners with special educational requirements. The integration of XR and generative AI offers transformative potential by creating adaptive, immersive, and inclusive learning environments. This approach ensures real-time adaptability to individual progress and accessibility, addressing critical barriers such as static content and lack of inclusivity in existing systems. The research outlines a pathway toward more inclusive and equitable education, significantly enhancing opportunities for learners with diverse needs and contributing to broader social integration and equity in education. © 2025 by the authors.
Intawong, K.; Worragin, P.; Khanchai, S.; Puritat, K.
Transformative Metaverse Pedagogy for Intangible Heritage: A Gamified Platform for Learning Lanna Dance in Immersive Cultural Education Journal Article
In: Education Sciences, vol. 15, no. 6, 2025, ISSN: 22277102 (ISSN).
Abstract | Links | BibTeX | Tags: Adaptive Learning, AI-assisted education, cultural preservation, Gamification, intangible cultural heritage, Lanna dance, Metaverse
@article{intawong_transformative_2025,
title = {Transformative Metaverse Pedagogy for Intangible Heritage: A Gamified Platform for Learning Lanna Dance in Immersive Cultural Education},
author = {K. Intawong and P. Worragin and S. Khanchai and K. Puritat},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105009306705&doi=10.3390%2feducsci15060736&partnerID=40&md5=9f17583b77ec54c090e50575b539f0c9},
doi = {10.3390/educsci15060736},
issn = {22277102 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Education Sciences},
volume = {15},
number = {6},
abstract = {This study explores the design of Metaverse technologies for preserving and teaching Lanna Dance, a traditional cultural heritage of Northern Thailand. It addresses the challenges of sustaining intangible cultural heritage by developing an immersive learning system that integrates motion capture, generative AI, and gamified virtual environments. Grounded in Situated Learning Theory and adaptive learning, the platform features four interactive zones, the Motion Showcase, Knowledge Exhibition, Video and AI Interaction, and Interactive Game Zone, offering learners multifaceted, context-rich experiences. Using a quasi-experimental design with 36 participants, the study evaluates learning outcomes, motivation, and user satisfaction. Results show significant improvements in knowledge acquisition and intrinsic motivation, along with high usability scores, indicating the effectiveness of immersive digital environments in enhancing cultural appreciation and skill development. The findings offer practical insights into Metaverse design for immersive cultural education, supporting educators, cultural institutions, and policymakers in developing scalable and engaging solutions for preserving intangible heritage through emerging technologies. © 2025 by the authors.},
keywords = {Adaptive Learning, AI-assisted education, cultural preservation, Gamification, intangible cultural heritage, Lanna dance, Metaverse},
pubstate = {published},
tppubtype = {article}
}
This study explores the design of Metaverse technologies for preserving and teaching Lanna Dance, a traditional cultural heritage of Northern Thailand. It addresses the challenges of sustaining intangible cultural heritage by developing an immersive learning system that integrates motion capture, generative AI, and gamified virtual environments. Grounded in Situated Learning Theory and adaptive learning, the platform features four interactive zones, the Motion Showcase, Knowledge Exhibition, Video and AI Interaction, and Interactive Game Zone, offering learners multifaceted, context-rich experiences. Using a quasi-experimental design with 36 participants, the study evaluates learning outcomes, motivation, and user satisfaction. Results show significant improvements in knowledge acquisition and intrinsic motivation, along with high usability scores, indicating the effectiveness of immersive digital environments in enhancing cultural appreciation and skill development. The findings offer practical insights into Metaverse design for immersive cultural education, supporting educators, cultural institutions, and policymakers in developing scalable and engaging solutions for preserving intangible heritage through emerging technologies. © 2025 by the authors.
2024
Domenichini, D.; Bucchiarone, A.; Chiarello, F.; Schiavo, G.; Fantoni, G.
An AI-Driven Approach for Enhancing Engagement and Conceptual Understanding in Physics Education Proceedings Article
In: IEEE Global Eng. Edu. Conf., EDUCON, IEEE Computer Society, 2024, ISBN: 21659559 (ISSN); 979-835039402-3 (ISBN).
Abstract | Links | BibTeX | Tags: Adaptive Learning, Artificial intelligence, Artificial intelligence in education, Artificial Intelligence in Education (AIED), Conceptual Understanding, Educational System, Educational systems, Gamification, Generative AI, generative artificial intelligence, Learning Activity, Learning systems, Physics Education, Teachers', Teaching, Virtual Reality
@inproceedings{domenichini_ai-driven_2024,
title = {An AI-Driven Approach for Enhancing Engagement and Conceptual Understanding in Physics Education},
author = {D. Domenichini and A. Bucchiarone and F. Chiarello and G. Schiavo and G. Fantoni},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199035695&doi=10.1109%2fEDUCON60312.2024.10578670&partnerID=40&md5=4cf9f89e97664ae6d618a90f2dbc23e0},
doi = {10.1109/EDUCON60312.2024.10578670},
isbn = {21659559 (ISSN); 979-835039402-3 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {IEEE Global Eng. Edu. Conf., EDUCON},
publisher = {IEEE Computer Society},
abstract = {This Work in Progress paper introduces the design of an innovative educational system that leverages Artificial Intelligence (AI) to address challenges in physics education. The primary objective is to create a system that dynamically adapts to the individual needs and preferences of students while maintaining user-friendliness for teachers, allowing them to tailor their teaching methods. The emphasis is on fostering motivation and engagement, achieved through the implementation of a gamified virtual environment and a strong focus on personalization. Our aim is to develop a system capable of autonomously generating learning activities and constructing effective learning paths, all under the supervision and interaction of teachers. The generation of learning activities is guided by educational taxonomies that delineate and categorize the cognitive processes involved in these activities. The proposed educational system seeks to address challenges identified by Physics Education Research (PER), which offers valuable insights into how individuals learn physics and provides strategies to enhance the overall quality of physics education. Our specific focus revolves around two crucial aspects: concentrating on the conceptual understanding of physics concepts and processes, and fostering knowledge integration and coherence across various physics topics. These aspects are deemed essential for cultivating enduring knowledge and facilitating practical applications in the field of physics. © 2024 IEEE.},
keywords = {Adaptive Learning, Artificial intelligence, Artificial intelligence in education, Artificial Intelligence in Education (AIED), Conceptual Understanding, Educational System, Educational systems, Gamification, Generative AI, generative artificial intelligence, Learning Activity, Learning systems, Physics Education, Teachers', Teaching, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This Work in Progress paper introduces the design of an innovative educational system that leverages Artificial Intelligence (AI) to address challenges in physics education. The primary objective is to create a system that dynamically adapts to the individual needs and preferences of students while maintaining user-friendliness for teachers, allowing them to tailor their teaching methods. The emphasis is on fostering motivation and engagement, achieved through the implementation of a gamified virtual environment and a strong focus on personalization. Our aim is to develop a system capable of autonomously generating learning activities and constructing effective learning paths, all under the supervision and interaction of teachers. The generation of learning activities is guided by educational taxonomies that delineate and categorize the cognitive processes involved in these activities. The proposed educational system seeks to address challenges identified by Physics Education Research (PER), which offers valuable insights into how individuals learn physics and provides strategies to enhance the overall quality of physics education. Our specific focus revolves around two crucial aspects: concentrating on the conceptual understanding of physics concepts and processes, and fostering knowledge integration and coherence across various physics topics. These aspects are deemed essential for cultivating enduring knowledge and facilitating practical applications in the field of physics. © 2024 IEEE.
Sarshartehrani, F.; Mohammadrezaei, E.; Behravan, M.; Gracanin, D.
Enhancing E-Learning Experience Through Embodied AI Tutors in Immersive Virtual Environments: A Multifaceted Approach for Personalized Educational Adaptation Proceedings Article
In: R.A., Sottilare; J., Schwarz (Ed.): Lect. Notes Comput. Sci., pp. 272–287, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 03029743 (ISSN); 978-303160608-3 (ISBN).
Abstract | Links | BibTeX | Tags: Adaptive Learning, Artificial intelligence, Artificial intelligence in education, Computer aided instruction, Computer programming, E - learning, E-Learning, Education computing, Embodied artificial intelligence, Engineering education, Immersive Virtual Environments, Learner Engagement, Learning experiences, Learning systems, Multi-faceted approach, Personalized Instruction, Traditional boundaries, Virtual Reality
@inproceedings{sarshartehrani_enhancing_2024,
title = {Enhancing E-Learning Experience Through Embodied AI Tutors in Immersive Virtual Environments: A Multifaceted Approach for Personalized Educational Adaptation},
author = {F. Sarshartehrani and E. Mohammadrezaei and M. Behravan and D. Gracanin},
editor = {Sottilare R.A. and Schwarz J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196174389&doi=10.1007%2f978-3-031-60609-0_20&partnerID=40&md5=3801d0959781b1a191a3eb14f47bd8d8},
doi = {10.1007/978-3-031-60609-0_20},
isbn = {03029743 (ISSN); 978-303160608-3 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {14727 LNCS},
pages = {272–287},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {As digital education transcends traditional boundaries, e-learning experiences are increasingly shaped by cutting-edge technologies like artificial intelligence (AI), virtual reality (VR), and adaptive learning systems. This study examines the integration of AI-driven personalized instruction within immersive VR environments, targeting enhanced learner engagement-a core metric in online education effectiveness. Employing a user-centric design, the research utilizes embodied AI tutors, calibrated to individual learners’ emotional intelligence and cognitive states, within a Python programming curriculum-a key area in computer science education. The methodology relies on intelligent tutoring systems and personalized learning pathways, catering to a diverse participant pool from Virginia Tech. Our data-driven approach, underpinned by the principles of educational psychology and computational pedagogy, indicates that AI-enhanced virtual learning environments significantly elevate user engagement and proficiency in programming education. Although the scope is limited to a single academic institution, the promising results advocate for the scalability of such AI-powered educational tools, with potential implications for distance learning, MOOCs, and lifelong learning platforms. This research contributes to the evolving narrative of smart education and the role of large language models (LLMs) in crafting bespoke educational experiences, suggesting a paradigm shift towards more interactive, personalized e-learning solutions that align with global educational technology trends. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
keywords = {Adaptive Learning, Artificial intelligence, Artificial intelligence in education, Computer aided instruction, Computer programming, E - learning, E-Learning, Education computing, Embodied artificial intelligence, Engineering education, Immersive Virtual Environments, Learner Engagement, Learning experiences, Learning systems, Multi-faceted approach, Personalized Instruction, Traditional boundaries, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
As digital education transcends traditional boundaries, e-learning experiences are increasingly shaped by cutting-edge technologies like artificial intelligence (AI), virtual reality (VR), and adaptive learning systems. This study examines the integration of AI-driven personalized instruction within immersive VR environments, targeting enhanced learner engagement-a core metric in online education effectiveness. Employing a user-centric design, the research utilizes embodied AI tutors, calibrated to individual learners’ emotional intelligence and cognitive states, within a Python programming curriculum-a key area in computer science education. The methodology relies on intelligent tutoring systems and personalized learning pathways, catering to a diverse participant pool from Virginia Tech. Our data-driven approach, underpinned by the principles of educational psychology and computational pedagogy, indicates that AI-enhanced virtual learning environments significantly elevate user engagement and proficiency in programming education. Although the scope is limited to a single academic institution, the promising results advocate for the scalability of such AI-powered educational tools, with potential implications for distance learning, MOOCs, and lifelong learning platforms. This research contributes to the evolving narrative of smart education and the role of large language models (LLMs) in crafting bespoke educational experiences, suggesting a paradigm shift towards more interactive, personalized e-learning solutions that align with global educational technology trends. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.