AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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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.
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.
Armony, Y.; Hazzan, O.
Springer Nature, 2024, ISBN: 978-303172790-0 (ISBN); 978-303172789-4 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence in education, Augmented Reality, Characteristics of technology, Educational reform, generative artificial intelligence, Inevitable technology, Virtual Reality
@book{armony_inevitability_2024,
title = {Inevitability of AI technology in education: Futurism perspectives for education for the next two decades},
author = {Y. Armony and O. Hazzan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105001750559&doi=10.1007%2f978-3-031-72790-0&partnerID=40&md5=7c7d979b5d48a1abd8830708a5b27d89},
doi = {10.1007/978-3-031-72790-0},
isbn = {978-303172790-0 (ISBN); 978-303172789-4 (ISBN)},
year = {2024},
date = {2024-01-01},
publisher = {Springer Nature},
series = {Inevitability of AI Technology in Education: Futurism Perspectives for Education for the Next Two Decades},
abstract = {This book layouts historic and future perspectives at the introduction of technology into education systems: On the one hand, the book attempts to explain why despite numerous attempts, technology has struggled to integrate successfully into the education system for over a century; on the other hand, it explores whether this trend will persist in the foreseeable future, questioning if emerging technologies, like virtual reality or Gen-AI will ever be embraced by education systems worldwide, and introducing a hypothesis that these technologies will become inevitable so that education systems will have a little choice in adopting them. The underlying perspective is that education systems need to prepare for this new future and better start doing so now. The book encompasses three key areas: education, technology, and future studies, with a focus on how technology will shape the future of education. It begins by examining past failures of integrating technology into education, analyzing the reasons behind these setbacks. It progresses to assess the potential integration of future technologies (10-20 years from now), exploring a feasible scenario and the force implications on learning, teachers, and the system. Examining recent attempts to implement technology in education reveals numerous reasons for failure. A significant contributing factor appears to be inherent conflicts within the education system's fundamental structure. These conflicts, involving goals, curricula, organizational structure, pedagogy, and student management, prevent the system from embracing reforms or new technologies. Envisioning a future where technology will deeply 'know' the students, 'sense' their environment, 'understand' the context and the situation, 'explain' and 'advise' them on the best suitable behavior or activity, the book anticipates applications in education ranging from ensuring personal safety and health to enhancing knowledge acquisition and decision-making. As the book explores the potential inevitability of technology in education, it recognizes the transformative impact on teachers and students and outlines possible desire scenario to aid in preparation, such as, personalized education to better suit student's capabilities, needs, and desires; how to motivate students to learn in an environment where all tasks can be done by machines; ethical issues; the new role of the school, the educator, and the system, etc. This book is especially suitable for teachers, educators, public officials, and anyone interested in the future of education. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. All rights reserved.},
keywords = {Artificial intelligence in education, Augmented Reality, Characteristics of technology, Educational reform, generative artificial intelligence, Inevitable technology, Virtual Reality},
pubstate = {published},
tppubtype = {book}
}
This book layouts historic and future perspectives at the introduction of technology into education systems: On the one hand, the book attempts to explain why despite numerous attempts, technology has struggled to integrate successfully into the education system for over a century; on the other hand, it explores whether this trend will persist in the foreseeable future, questioning if emerging technologies, like virtual reality or Gen-AI will ever be embraced by education systems worldwide, and introducing a hypothesis that these technologies will become inevitable so that education systems will have a little choice in adopting them. The underlying perspective is that education systems need to prepare for this new future and better start doing so now. The book encompasses three key areas: education, technology, and future studies, with a focus on how technology will shape the future of education. It begins by examining past failures of integrating technology into education, analyzing the reasons behind these setbacks. It progresses to assess the potential integration of future technologies (10-20 years from now), exploring a feasible scenario and the force implications on learning, teachers, and the system. Examining recent attempts to implement technology in education reveals numerous reasons for failure. A significant contributing factor appears to be inherent conflicts within the education system's fundamental structure. These conflicts, involving goals, curricula, organizational structure, pedagogy, and student management, prevent the system from embracing reforms or new technologies. Envisioning a future where technology will deeply 'know' the students, 'sense' their environment, 'understand' the context and the situation, 'explain' and 'advise' them on the best suitable behavior or activity, the book anticipates applications in education ranging from ensuring personal safety and health to enhancing knowledge acquisition and decision-making. As the book explores the potential inevitability of technology in education, it recognizes the transformative impact on teachers and students and outlines possible desire scenario to aid in preparation, such as, personalized education to better suit student's capabilities, needs, and desires; how to motivate students to learn in an environment where all tasks can be done by machines; ethical issues; the new role of the school, the educator, and the system, etc. This book is especially suitable for teachers, educators, public officials, and anyone interested in the future of education. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. All rights reserved.