Humanizing Online Learning: The Role of AI+XR-Based Virtual Tutors in Adaptive Education
Resumo
The integration of Artificial Intelligence (AI) and Extended Reality (XR) in education has opened new possibilities for adaptive and personalized learning. Among these, Virtual Humans (VH), which are AI-driven XR avatars capable of real-time humanized interaction, have emerged as promising tools for content adaptation, emotional support, and learner engagement. This paper examines the roles of VH in fostering adaptive learning, emphasizing their capability to meet diverse learner needs through responsive, individualized content adaptations, based on a literature review. This study investigates the effectiveness of a VH-based system, VirtualTutor, developed to enhance online learning in a Computer Science course. A case study involving 265 undergraduate students evaluated the impact of the system on engagement, perceived usefulness, and comprehension. The results of this study are presented in this paper. Findings support the potential of VH to foster inclusive, scalable, and learner-centered educational environments, while also identifying key areas for system refinement and future research.
Palavras-chave:
AI-based Learning, Virtual Humans, Extended Reality, Adaptive Learning, Personalized Instruction, Virtual Tutors
Referências
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N. Sabharwal and A. Agrawal, "Introduction to Google Dialogflow," in Cognitive Virtual Assistants Using Google Dialogflow, 1st ed. Chapman and Hall/CRC, 2020, pp. 13-54.
J. Kocoń et al., "ChatGPT: Jack of All Trades, Master of None," Information Fusion, vol. 99, p. 101861, 2023.
N. van der Meer, V. van der Werf, W. P. Brinkman, and M. Specht, “Virtual reality and collaborative learning: A systematic literature review,” Frontiers in Virtual Reality, vol. 4, Art. no. 1159905, 2023.
C. Hayles, "Crafting Realistic Virtual Humans: Unveiling Perspectives on Human Interaction in Education," IEEE Transactions on Learning Technologies, vol. 15, no. 3, pp. 215-225, Aug. 2023. DOI: 10.1109/TLT.2023.3145567.
D. Burden and M. Savin-Baden, Virtual Humans: Today and Tomorrow. Boca Raton, FL, USA: Chapman and Hall/CRC, 2019..
R. Roig-Vila, M. Cazorla, and S. Lallé, “Methodology for emotion-aware education based on artificial intelligence,” Frontiers in Artificial Intelligence, vol. 8, Art. no. 1704389, 2025..
S. K. D'Mello and A. Graesser, "AutoTutor and Affective AutoTutor: Learning by Talking with Cognitively and Emotionally Intelligent Computers That Talk Back," ACM Transactions on Interactive Intelligent Systems, vol. 2, no. 4, pp. 23-40, 2019.
Y. C. Huang, "Comparison and contrast of Piaget and Vygotsky’s theories," in Proc. 7th Int. Conf. Humanit. Social Sci. Res. (ICHSSR), May 2021, pp. 28–32.
D. P. Ausubel, Educational Psychology: A Cognitive View, 2nd ed. New York: Holt, Rinehart and Winston, 1978.
F. Martin, Y. Chen, R. L. Moore, and C. D. Westine, “Systematic review of adaptive learning research designs, context, strategies, and technologies from 2009 to 2018,” Educational Technology Research and Development, vol. 68, no. 4, pp. 1903–1929, 2020.
F. Li, Y. He, and Q. Xue, “Progress, challenges and countermeasures of adaptive learning,” Educational Technology & Society, vol. 24, no. 3, pp. 238–255, 2021..
Y. E. Rachmad, Adaptive Learning Theory, La Paz: Costanera Publicaciones Internacionales, Ed. Esp. 2022. [Online]. DOI: 10.17605/osf.io/vfz38
S. Minn, “AI-assisted knowledge assessment techniques for adaptive learning environments,” Computers and Education: Artificial Intelligence, vol. 3, p. 100050, 2022.
Ł. Tomczyk and S. Sunday Oyelere, ICT for Learning and Inclusion in Latin America and Europe. Case Study From Countries: Bolivia, Brazil, Cuba, Dominican Republic, Ecuador, Finland, Poland, Turkey, Uruguay, 2019.
M. M. Rathore, S. A. Shah, D. Shukla, E. Bentafat, and S. Bakiras, "The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities," IEEE Access, vol. 9, pp. 32030-32052, 2021.
P. Radanliev, D. De Roure, P. Novitzky, and I. Sluganovic, "Accessibility and Inclusiveness of New Information and Communication Technologies for Disabled Users and Content Creators in the Metaverse," Disability and Rehabilitation: Assistive Technology, vol. 19, no. 5, pp. 1849-1863, 2024.
A. Chalkiadakis, A. Seremetaki, A. Kanellou, M. Kallishi, A. Morfopoulou, M. Moraitaki, and S. Mastrokoukou, "Impact of artificial intelligence and virtual reality on educational inclusion: A systematic review of technologies supporting students with disabilities," *Education Sciences*, vol. 14, no. 11, p. 1223, 2024.
M. Hmoud, W. Daher, and A. Ayyoub, "The Impact of AI, XR, and Combined AI-XR on Student Satisfaction: A Moderated Mediation Analysis of Engagement and Learner Characteristics," IEEE Access, 2025.
M. Worsley, D. Barel, L. Davison, T. Large, and T. Mwiti, "Multimodal Interfaces for Inclusive Learning," in Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II, Springer International Publishing, pp. 389-393.
J. R. Thompson, V. L. Walker, K. A. Shogren, and M. L. Wehmeyer, "Expanding Inclusive Educational Opportunities for Students with the Most Significant Cognitive Disabilities Through Personalized Supports," Intellectual and Developmental Disabilities, vol. 56, no. 6, pp. 396-411, 2018.
J. C. Lester, S. A. Towns, C. Callaway, J. H. Voerman, and P. Fitzgerald, "Deictic and Emotive Communication in Animated Pedagogical Agents," in Proceedings of the AAAI-98/IAAI-98, pp. 1043-1049, Madison, 1998.
O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, "Systematic Review of Research on Artificial Intelligence Applications in Higher Education – Where Are the Educators?," International Journal of Educational Technology in Higher Education, vol. 16, no. 1, pp. 1-27, 2019.
A. Paiva, I. Leite, H. Boukricha, and I. Wachsmuth, "Empathy in Virtual Agents and Robots: A Survey," ACM Transactions on Interactive Intelligent Systems, vol. 7, no. 3, pp. 1-40, 2017.
D. Burden and M. Savin-Baden, Virtual Humans: Today and Tomorrow, Chapman and Hall/CRC, 2019.
T. W. Bickmore and R. W. Picard, "Establishing and Maintaining Long-Term Human-Computer Relationships," ACM Transactions on Computer-Human Interaction, vol. 12, no. 2, pp. 293-327, 2019.
Z. Ersozlu, S. Ledger, A. Ersozlu, F. Mayne, and H. Wildy, "Mixed-Reality Learning Environments in Teacher Education: An Analysis of TeachLivE™ Research," Sage Open, vol. 11, no. 3, p. 21582440211032155, 2021.
G. Biswas, D. Leelawong, B. Schwartz, N. Vye, and The Teachable Agents Group at Vanderbilt, "Learning by Teaching: A New Agent Paradigm for Educational Software," Applied Artificial Intelligence, vol. 19, no. 3, pp. 363-392, 2018.
N. Sabharwal and A. Agrawal, "Introduction to Google Dialogflow," in Cognitive Virtual Assistants Using Google Dialogflow, 1st ed. Chapman and Hall/CRC, 2020, pp. 13-54.
J. Kocoń et al., "ChatGPT: Jack of All Trades, Master of None," Information Fusion, vol. 99, p. 101861, 2023.
Publicado
22/10/2025
Como Citar
CARDOSO, Alexandre; SIQUEIRA, Alexandre Gomes de; MARTINS, Valéria Farinazzo; OLIVEIRA NETO, João Soares de; ELISEO, Maria Amelia; SILVEIRA, Ismar Frango.
Humanizing Online Learning: The Role of AI+XR-Based Virtual Tutors in Adaptive Education. In: CONGRESSO LATINO-AMERICANO DE SOFTWARE LIVRE E TECNOLOGIAS ABERTAS (LATINOWARE), 22. , 2025, Foz do Iguaçu/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 473-480.
DOI: https://doi.org/10.5753/latinoware.2025.16483.
