Triadic fusion: investigating the educational impact of AI, AR, and NLP integration in creating immersive and conversational learning environments
Abstract
This study introduces Triadic Fusion—a novel framework that integrates Artificial Intelligence (AI), Augmented Reality (AR), and Natural Language Processing (NLP) to create immersive and conversational learning environments. Unlike existing multimodal or cross-technology models, Triadic Fusion is grounded in constructivist, socio-cultural, and cognitive load theories, aligning technological orchestration with pedagogical intent across cognitive, contextual, and communicative domains. Using a mixed-methods approach, we studied 120 students and 10 educators through pre- and post-assessments, surveys, classroom observations, and interviews. The framework was applied across diverse disciplines and educational levels. Results demonstrated that Triadic Fusion significantly enhanced student engagement, content comprehension, and collaborative learning outcomes. Educators reported improvements in personalization and interactive teaching. This research contributes both theoretically and practically by differentiating Triadic Fusion from prior models and demonstrating its empirical benefits. It offers actionable insights for educators, technologists, and policymakers developing the next generation of immersive educational technologies.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Machine learning: Algorithms, real-world applications and research directions
Sarker, I. H. (2021) · SN Computer Science · doi:10.1007/s42979-021-00592-x · Cited by 5,583 · cited 2× · see citing works
“For example, Koumpouros (2024) highlights the potential of AR for engaging content delivery, while Sarker (2021) underscores the role of AI and NLP in personalized learning.”
Understanding the role of digital technologies in education: A review
Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022) · Sustainable Operations and Computers · doi:10.1016/j.susoc.2022.05.004 · Cited by 2,647 · see citing works
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463 · cited 1× · see citing works
“NLP has been extensively studied in various contexts, including educational chatbots, automated writing feedback, and speech-based tutoring systems (Gill & Kaur, 2023; Ray, 2023).”
Natural language processing: state of the art, current trends and challenges
Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13428-4 · Cited by 1,823 · see citing works
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363 · see citing works
State of the art and practice in <scp>AI</scp> in education
Holmes, W., & Tuomi, I. (2022) · European Journal of Education · doi:10.1111/ejed.12533 · Cited by 1,093 · cited 2× · see citing works
“Few implementations are grounded in constructivist or socio-cultural learning paradigms, and even fewer account for HCI and cognitive load design principles (Holmes & Tuomi, 2022; Zhang & Aslan, 2021).”
AI technologies for education: Recent research & future directions
Zhang, K., & Aslan, A. B. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100025 · Cited by 923 · see citing works
Analyzing augmented reality (AR) and virtual reality (VR) recent development in education
Al‐Ansi, A. M., Jaboob, M. S., Garad, A., & Al-Ansi, A. (2023) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2023.100532 · Cited by 703 · see citing works
Alqahtani, T., Badreldin, H. A., Alrashed, M., Alshaya, A. I., Alghamdi, S. S., bin Saleh, K., Alowais, S. A., Alshaya, O. A., Rahman, I., Al Yami, M. S., et al. (2023) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2023.05.016 · Cited by 565 · see citing works
Liang, J.-C., Hwang, G.-J., Chen, M.-R. A., & Darmawansah, D. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2021.1958348 · Cited by 378 · see citing works
Dai, C., & Ke, F. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100087 · Cited by 319 · see citing works
ChatGPT: Empowering lifelong learning in the digital age of higher education
Rawas, S. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12114-8 · Cited by 310 · see citing works
Self-citationChatGPT: Vision and challenges
Gill, S. S., & Kaur, R. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.05.004 · Cited by 265 · see citing works
Conceptualizing the emerging field of smart learning environments
Spector, J. M. (2014) · Smart Learning Environments · doi:10.1186/s40561-014-0002-7 · Cited by 251 · see citing works
Samala, A. D., Rawas, S., Wang, T., Reed, J. M., Kim, J., Howard, N.-J., & Ertz, M. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12936-0 · Cited by 229 · cited 1× · see citing works
“NLP, a subset of AI, allows machines to process and respond to human language, fostering conversational interactions and automated language analysis (Fui-Hoon Nah et al., 2023; Rawas, 2023; Samala & Rawas, 2024).”
Self-citationArtificial intelligence powered Metaverse: analysis, challenges and future perspectives
Soliman, M., Ahmed, E., Darwish, A., & Hassanien, A. E. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-023-10641-x · Cited by 175 · see citing works
Revealing the true potential and prospects of augmented reality in education
Koumpouros, Y. (2024) · Smart Learning Environments · doi:10.1186/s40561-023-00288-0 · Cited by 151 · see citing works
Collaborative generative learning activities in immersive virtual reality increase learning
Petersen, G. B., Stenberdt, V. A., Mayer, R. E., & Makransky, G. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104931 · Cited by 121 · see citing works
The optimistic future of Artificial Intelligence in higher education
Escotet, M. Á. (2024) · PROSPECTS · doi:10.1007/s11125-023-09642-z · Cited by 107 · see citing works
Technology and innovation in shaping the future of education
Çelık, F., & Baturay, M. H. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00339-0 · Cited by 95 · see citing works
Radosavljević, S., Radosavljević, V., & Grgurović, B. (2018) · Interactive Learning Environments · doi:10.1080/10494820.2018.1528286 · Cited by 87 · see citing works
The Evolution of HCI and Human Factors: Integrating Human and Artificial Intelligence
Chignell, M., Wang, L., Zare, A., & Li, J. J. (2022) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3557891 · Cited by 77 · see citing works
An In-Depth Review of ChatGPT’s Pros and Cons for Learning and Teaching in Education
Samala, A. D., Zhaı, X., Aoki, K., Bojić, L., & Žikić, S. (2024) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v18i02.46509 · Cited by 75 · see citing works
Self-citationKökver, Y., Pektaş, H. M., & Çelik, H. (2024) · Education and Information Technologies : Official Journal of the IFIP technical committee on Education · doi:10.1007/s10639-024-12919-1 · Cited by 54 · see citing works
Kalemkuş, J., & Kalemkuş, F. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2022.2027458 · Cited by 49 · see citing works
Generative AI as Virtual Healthcare Assistant for Enhancing Patient Care Quality
Samala, A. D., & Rawas, S. (2024) · International Journal of Online and Biomedical Engineering (iJOE) · doi:10.3991/ijoe.v20i05.45937 · Cited by 42 · see citing works
Self-citationAI and Emotional Intelligence for Modern Business Management
(2023) · Advances in logistics, operations, and management science book series · doi:10.4018/979-8-3693-0418-1 · Cited by 38 · see citing works
Romano, M., Dı́az, P., & Aedo, I. (2020) · Interactive Learning Environments · doi:10.1080/10494820.2020.1851727 · Cited by 36 · see citing works
Test-Taker Engagement in AI Technology-Mediated Language Assessment
Jin, Y., & Fan, J. J. (2023) · Language Assessment Quarterly · doi:10.1080/15434303.2023.2291731 · Cited by 27 · see citing works
An AI-powered conversational system for college students learning English as a second language
Dai, L., & Wu, F. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13640-3 · Cited by 27 · see citing works
Rashid, M. T., Wei, N., & Wang, D. (2023) · Collective Intelligence · doi:10.1177/26339137231170825 · Cited by 26 · see citing works
MEinVR: Multimodal interaction techniques in immersive exploration
Yuan, Z., He, S., Liu, Y., & Yu, L. (2023) · Visual Informatics · doi:10.1016/j.visinf.2023.06.001 · Cited by 26 · see citing works
Personalized smart immersive XR environments: a systematic literature review
Huang, N., Goswami, P., Sundstedt, V., Hu, Y. Q., & Cheddad, A. (2025) · The Visual Computer · doi:10.1007/s00371-025-03887-9 · Cited by 19 · see citing works
Wang, D., Shan, D., Ju, R., Kao, B., Zhang, C., & Chen, G. (2024) · Education and Information Technologies · doi:10.1007/s10639-024-13195-9 · Cited by 13 · see citing works
Alhazzaa, K., & Yan, W. (2025) · Computers & Education X Reality · doi:10.1016/j.cexr.2025.100097 · Cited by 12 · see citing works
Park, S. (2023) · Routledge eBooks · doi:10.4324/9781003266365-13 · Cited by 10 · see citing works
Application of Immersive Technologies in Primary and Secondary Education
Jin, S., Huang, J.-B., & Zhong, Z. (2024) · Frontiers of digital education. · doi:10.1007/s44366-024-0001-3 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Serin, M. K., & Kepceoğlu, İ. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2573746 · Cited by 12 · see citing works
Semerikov, S. O., & Semerikov, S. O. (2026) · Discover Education · doi:10.1007/s44217-026-01179-5 · Cited by 9 · see citing works
Wan, K., Woo, Y. Y., & Ho, G. T. S. (2025) · Cogent Education · doi:10.1080/2331186x.2025.2592370 · Cited by 3 · see citing works
“This trajectory is echoed by Samala and Rawas (2025), who highlight how the integration of AI with other technologies — such as Augmented Reality (AR) and Natural Language Processing (NLP) — can foster immersive, conversational, and experiential learning environments that deepen student engagement.”
Chauhan, R., & Patel, A. (2026) · Discover Education · doi:10.1007/s44217-026-01185-7
Wang, Y., & Liao, Z. (2025) · International Conference on Artificial Intelligence, Digital Media Technology and Interaction Design (ICADI) · doi:10.1145/3795926.3795978
- Authors
- Samala, A. D., & Rawas, S.
- Affiliations
- Universitas Negeri Padang (ID)
- Beirut Arab University (LB)
- Corresponding author
- Samala, Agariadne Dwinggo
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2025-09-06
- Volume
- 34
- Issue
- 5
- Pages
- 2794-2809
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W4414035926
- Cited by
- 5
- References
- 37
- Citations by year
- 2026: 2 · 2025: 3
- FWCI
- 1.77
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Interactive Learning Environments (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Keywords
- artificial intelligence in education, augmented reality, natural language processing, immersive learning environments, conversational learning, constructivism, sociocultural theory, cognitive load theory, student engagement, cooperative learning, personalized learning, educational technology integration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
