Publications

@inproceedings{kadri_game-based_2025,

title = {Game-Based VR Anatomy Learning with Generative AI: Proof of Concept for GenAiVR-Lab},

author = {M. Kadri and F. -E. Boubakri and A. Azough and K. A. Zidani},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105015604062&doi=10.1109%2FSCME62582.2025.11104860&partnerID=40&md5=c557ca7975a9683e8c271fbb3a21c4e4},

doi = {10.1109/SCME62582.2025.11104860},

isbn = {9798331534899 (ISBN)},

year  = {2025},

date = {2025-01-01},

pages = {100–105},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Anatomy education often fails to engage learners or foster precise 3D spatial understanding of complex systems like the human skeleton. We present a Game-Based VR Anatomy Learning system with Generative AI, introduced as a Proof of Concept for our GenAiVR-Lab framework. This prototype validates the foundational pillars of our future development. In the Anatomy Lab scenario, 25 medical students explore a virtual skeleton and undertake a timed mission: assemble three bone fragments within two minutes. Incorrect picks are disabled with point deductions; learners may request a one-shot conversational hint from a ChatGPT-powered Virtual Anatomy Instructor; if time expires, a teammate continues with remaining time. We measured perception changes using pre- and post-test versions of four Perspective Questionnaires: Learning Perspective (LPQ), VR-AI Perspective (VRAIPQ), Generative AI Perspective (GAIPQ), and Game-Based Learning Perspective (GBLPQ). Results demonstrate significant improvements across all four perspectives, with mean scores increasing by approximately 1.3 points on the 5-point Likert scale and nearly all participants showing positive gains. Effect sizes ranged from 2.52 to 3.34, indicating large practical significance, with all measures reaching statistical significance. These findings demonstrate that collaborative game mechanics and generative AI guidance enhance engagement and spatial reasoning. We contrast this PoC with the full GenAiVR-Lab vision - integrating Retrieval-Augmented Generation for precise feedback, multimodal I/O, and adaptive pathways - and outline a roadmap for next-generation immersive anatomy education. © 2025 Elsevier B.V., All rights reserved.},

keywords = {Anatomy educations, Artificial intelligence, Bone, Bone fragments, Collaborative learning, E-Learning, Educational Evaluation, Game-Based, Game-based learning, Generative AI, Human computer interaction, Human skeleton, Laboratories, Learning systems, Medical students, Proof of concept, Virtual Reality, Virtual Reality Anatomy},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{boubakri_exploring_2025,

title = {Exploring 3D Cardiac Anatomy with Text-Based AI Guidance in Virtual Reality},

author = {F. -E. Boubakri and M. Kadri and F. Z. Kaghat and A. Azough and H. Tairi},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105015676741&doi=10.1109%2FSCME62582.2025.11104869&partnerID=40&md5=c961694f97c50adc23b6826dddb265cd},

doi = {10.1109/SCME62582.2025.11104869},

isbn = {9798331534899 (ISBN)},

year  = {2025},

date = {2025-01-01},

pages = {43–48},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {This paper presents the design and development of a social virtual reality (VR) classroom focused on cardiac anatomy education for students in grades K-12. The application allows multiple learners to explore a detailed 3D heart model within an immersive and collaborative environment. A crucial part of the system is the integration of a text-based conversational AI interface powered by ChatGPT, which provides immediate, interactive explanations and addresses student inquiries about heart anatomy. The system supports both guided and exploratory learning modes, encourages peer collaboration, and offers personalized support through natural language dialogue. We evaluated the system's effectiveness through a comprehensive study measuring learning perception (LPQ), VR perception (VRPQ), AI perception (AIPQ), and VR-related symptoms (VRSQ). Potential applications include making high-quality cardiac anatomy education more affordable for K-12 schools with limited resources, offering an adaptable AI-based tutoring system for students to learn at their own pace, and equipping educators with an easy-to-use tool to integrate into their science curriculum with minimal additional training. © 2025 Elsevier B.V., All rights reserved.},

keywords = {3D cardiac anatomy, 3d heart models, Anatomy education, Anatomy educations, Cardiac anatomy, Collaborative environments, Collaborative learning, Computer aided instruction, Curricula, Design and Development, E-Learning, Education computing, Generative AI, Heart, Immersive environment, Learning systems, Natural language processing systems, Social virtual reality, Students, Teaching, Three dimensional computer graphics, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{harinee_elevating_2024,

title = {Elevating Medical Training: A Synergistic Fusion of AI and VR for Immersive Anatomy Learning and Practical Procedure Mastery},

author = {S. Harinee and R. Vimal Raja and E. Mugila and I. Govindharaj and V. Sanjaykumar and T. Ragavendhiran},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000334626&doi=10.1109%2FICSCAN62807.2024.10894451&partnerID=40&md5=ae7a491686ade8cebdc276f585a6f4f0},

doi = {10.1109/ICSCAN62807.2024.10894451},

isbn = {9798331510022 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Int. Conf. Syst., Comput., Autom. Netw., ICSCAN},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Virtual reality with its 3D visualization have brought an overwhelming change in the face of medical education, especially for courses like human anatomy. The proposed virtual reality system to bring massive improvements in the education received by a medical student studying for their degree courses. The project puts forward the text-to-speech and speech-to-text aligned system that simplifies the usage of a chatbot empowered by OpenAI GPT-4 and allows pupils to vocally speak with Avatar, the set virtual assistant. Contrary to the current methodologies, the setup of virtual reality is powered by avatars and thus covers an enhanced virtual assistant environment. Avatars offer students the set of repeated practicing of medical procedures on it, and the real uniqueness in the proposed product. The developed virtual reality environment is enhanced over other current training techniques where a student should interact and immerse in three-dimensional human organs for visualization in three dimensions and hence get better knowledge of the subjects in greater depth. A virtual assistant guides the whole process, giving insights and support to help the student bridge the gap from theory to practice. Then, the system is essentially Knowledge based and Analysis based approach. The combination of generative AI along with embodied virtual agents has great potential when it comes to customized virtual conversation assistant for much wider range of applications. The study brings out the value of acquiring hands-on skills through simulated medical procedures and opens new frontiers of research and development in AI, VR, and medical education. In addition to assessing the effectiveness of such novel functionalities, the study also explores user experience related dimensions such as usability, task loading, and the sense of presence in proposed virtual medical environment. © 2025 Elsevier B.V., All rights reserved.},

keywords = {'current, Anatomy education, Anatomy educations, Computer interaction, Curricula, Embodied virtual assistant, Embodied virtual assistants, Generative AI, Human- Computer Interaction, Immersive, Intelligent virtual agents, Medical computing, Medical education, Medical procedure practice, Medical procedures, Medical training, Personnel training, Students, Teaching, Three dimensional computer graphics, Usability engineering, Virtual assistants, Virtual environments, Virtual Reality, Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{chheang_towards_2024,

title = {Towards Anatomy Education with Generative AI-based Virtual Assistants in Immersive Virtual Reality Environments},

author = {V. Chheang and S. Sharmin and R. Marquez-Hernandez and M. Patel and D. Rajasekaran and G. Caulfield and B. Kiafar and J. Li and P. Kullu and R. L. Barmaki},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187216893&doi=10.1109%2FAIxVR59861.2024.00011&partnerID=40&md5=9b2e2671cdf57b4df3e4ac8a32fa4014},

doi = {10.1109/AIxVR59861.2024.00011},

isbn = {9798350372021 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Proc. - IEEE Int. Conf. Artif. Intell. Ext. Virtual Real., AIxVR},

pages = {21–30},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Virtual reality (VR) and interactive 3D visualization systems have enhanced educational experiences and environments, particularly in complicated subjects such as anatomy education. VR-based systems surpass the potential limitations of traditional training approaches in facilitating interactive engagement among students. However, research on embodied virtual assistants that leverage generative artificial intelligence (AI) and verbal communication in the anatomy education context is underrepresented. In this work, we introduce a VR environment with a generative AI-embodied virtual assistant to support participants in responding to varying cognitive complexity anatomy questions and enable verbal communication. We assessed the technical efficacy and usability of the proposed environment in a pilot user study with 16 participants. We conducted a within-subject design for virtual assistant configuration (avatar- and screen-based), with two levels of cognitive complexity (knowledge- and analysis-based). The results reveal a significant difference in the scores obtained from knowledge- and analysis-based questions in relation to avatar configuration. Moreover, results provide insights into usability, cognitive task load, and the sense of presence in the proposed virtual assistant configurations. Our environment and results of the pilot study offer potential benefits and future research directions beyond medical education, using generative AI and embodied virtual agents as customized virtual conversational assistants. © 2024 Elsevier B.V., All rights reserved.},

keywords = {3-D visualization systems, Anatomy education, Anatomy educations, Cognitive complexity, E-Learning, Embodied virtual assistant, Embodied virtual assistants, Generative AI, generative artificial intelligence, Human computer interaction, human-computer interaction, Immersive virtual reality, Interactive 3d visualizations, Knowledge Management, Medical education, Three dimensional computer graphics, Verbal communications, Virtual assistants, Virtual Reality, Virtual-reality environment},

pubstate = {published},

tppubtype = {inproceedings}

}