AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
How to
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
Vadisetty, R.; Polamarasetti, A.; Goyal, M. K.; Rongali, S. K.; Prajapati, S. K.; Butani, J. B.
Cloud-Based Immersive Learning: The Role of Virtual Reality, Big Data, and Generative AI in Transformative Education Experiences Proceedings Article
In: Mishra, S.; Tripathy, H. K.; Mohanty, J. R. (Ed.): Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331523022 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Big Data, Cloud analytics, Cloud environments, Cloud-based, Cloud-based learning, E-Learning, Engineering education, Generative AI, generative artificial intelligence, Immersive learning, Learning analytic, learning analytics, Learning systems, Metadata, Personalized Education, Personalized learning, Real time analysis, Realistic simulation, Virtual environments, Virtual Reality
@inproceedings{vadisetty_cloud-based_2025,
title = {Cloud-Based Immersive Learning: The Role of Virtual Reality, Big Data, and Generative AI in Transformative Education Experiences},
author = {R. Vadisetty and A. Polamarasetti and M. K. Goyal and S. K. Rongali and S. K. Prajapati and J. B. Butani},
editor = {S. Mishra and H. K. Tripathy and J. R. Mohanty},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105018048438&doi=10.1109%2FASSIC64892.2025.11158636&partnerID=40&md5=6d832a0f4460d2eb93e357faba143a32},
doi = {10.1109/ASSIC64892.2025.11158636},
isbn = {9798331523022 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Immersive learning transforms education by integrating Virtual Reality (VR), Big Data, and Generative Artificial Intelligence (AI) in cloud environments. This work discusses these technologies' contribution towards increased engagement, personalized learning, and recall through flexible and interactive experiences. Realistic simulations in a secure environment, real-time analysis via Big Data, and dynamically personalized information via Generative AI make immersive learning a reality. Nevertheless, scalability, security, and ease of integration are yet to be addressed. This article proposes an integrated model for cloud-based immersive learning, comparing conventional and AI-facilitated approaches through experimental evaluation. Besides, technical, ethical, and legislative considerations and future directions for inquiry are addressed. In conclusion, with its potential for personalized, scalable, and data-intensive instruction, AI-facilitated immersive learning is a transformational technology for educational delivery. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Artificial intelligence, Big Data, Cloud analytics, Cloud environments, Cloud-based, Cloud-based learning, E-Learning, Engineering education, Generative AI, generative artificial intelligence, Immersive learning, Learning analytic, learning analytics, Learning systems, Metadata, Personalized Education, Personalized learning, Real time analysis, Realistic simulation, Virtual environments, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
Immersive learning transforms education by integrating Virtual Reality (VR), Big Data, and Generative Artificial Intelligence (AI) in cloud environments. This work discusses these technologies' contribution towards increased engagement, personalized learning, and recall through flexible and interactive experiences. Realistic simulations in a secure environment, real-time analysis via Big Data, and dynamically personalized information via Generative AI make immersive learning a reality. Nevertheless, scalability, security, and ease of integration are yet to be addressed. This article proposes an integrated model for cloud-based immersive learning, comparing conventional and AI-facilitated approaches through experimental evaluation. Besides, technical, ethical, and legislative considerations and future directions for inquiry are addressed. In conclusion, with its potential for personalized, scalable, and data-intensive instruction, AI-facilitated immersive learning is a transformational technology for educational delivery. © 2025 Elsevier B.V., All rights reserved.
2024
Ivanova, M.; Grosseck, G.; Holotescu, C.
Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching Journal Article
In: Informatics, vol. 11, no. 1, 2024, ISSN: 22279709 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Abstract | Links | BibTeX | Tags: Artificial intelligence, ChatGPT, Intelligent Environment, large language models, learning analytics, Teaching
@article{ivanova_unveiling_2024,
title = {Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching},
author = {M. Ivanova and G. Grosseck and C. Holotescu},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188949348&doi=10.3390%2Finformatics11010010&partnerID=40&md5=528da77c867555fb0569ba6c14f887d1},
doi = {10.3390/informatics11010010},
issn = {22279709 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Informatics},
volume = {11},
number = {1},
abstract = {The penetration of intelligent applications in education is rapidly increasing, posing a number of questions of a different nature to the educational community. This paper is coming to analyze and outline the influence of artificial intelligence (AI) on teaching practice which is an essential problem considering its growing utilization and pervasion on a global scale. A bibliometric approach is applied to outdraw the “big picture” considering gathered bibliographic data from scientific databases Scopus and Web of Science. Data on relevant publications matching the query “artificial intelligence and teaching” over the past 5 years have been researched and processed through Biblioshiny in R environment in order to establish a descriptive structure of the scientific production, to determine the impact of scientific publications, to trace collaboration patterns and to identify key research areas and emerging trends. The results point out the growth in scientific production lately that is an indicator of increased interest in the investigated topic by researchers who mainly work in collaborative teams as some of them are from different countries and institutions. The identified key research areas include techniques used in educational applications, such as artificial intelligence, machine learning, and deep learning. Additionally, there is a focus on applicable technologies like ChatGPT, learning analytics, and virtual reality. The research also explores the context of application for these techniques and technologies in various educational settings, including teaching, higher education, active learning, e-learning, and online learning. Based on our findings, the trending research topics can be encapsulated by terms such as ChatGPT, chatbots, AI, generative AI, machine learning, emotion recognition, large language models, convolutional neural networks, and decision theory. These findings offer valuable insights into the current landscape of research interests in the field. © 2024 Elsevier B.V., All rights reserved.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
keywords = {Artificial intelligence, ChatGPT, Intelligent Environment, large language models, learning analytics, Teaching},
pubstate = {published},
tppubtype = {article}
}
The penetration of intelligent applications in education is rapidly increasing, posing a number of questions of a different nature to the educational community. This paper is coming to analyze and outline the influence of artificial intelligence (AI) on teaching practice which is an essential problem considering its growing utilization and pervasion on a global scale. A bibliometric approach is applied to outdraw the “big picture” considering gathered bibliographic data from scientific databases Scopus and Web of Science. Data on relevant publications matching the query “artificial intelligence and teaching” over the past 5 years have been researched and processed through Biblioshiny in R environment in order to establish a descriptive structure of the scientific production, to determine the impact of scientific publications, to trace collaboration patterns and to identify key research areas and emerging trends. The results point out the growth in scientific production lately that is an indicator of increased interest in the investigated topic by researchers who mainly work in collaborative teams as some of them are from different countries and institutions. The identified key research areas include techniques used in educational applications, such as artificial intelligence, machine learning, and deep learning. Additionally, there is a focus on applicable technologies like ChatGPT, learning analytics, and virtual reality. The research also explores the context of application for these techniques and technologies in various educational settings, including teaching, higher education, active learning, e-learning, and online learning. Based on our findings, the trending research topics can be encapsulated by terms such as ChatGPT, chatbots, AI, generative AI, machine learning, emotion recognition, large language models, convolutional neural networks, and decision theory. These findings offer valuable insights into the current landscape of research interests in the field. © 2024 Elsevier B.V., All rights reserved.