The use of immersive technologies such as virtual reality (VR), augmented reality (AR), mixed reality (MR), extended reality (XR), and metaverse-based learning environments is transforming higher education by offering interactive, experiential, and student-centered learning opportunities. Despite the fragmented literature, however, there is little clear understanding about the impact of these technologies on learning processes and outcomes. This work aims to address this gap with a narrative review of 39 papers published in peer-reviewed, Scopus-indexed journals on the use of immersive technologies in higher education. Five main clusters emerged from the thematic synthesis: cognitive engagement and deep learning; pedagogical and instructional innovation; affective and experiential learning; immersive systems with AI; and technology adoption and usability. The results suggest that the focus of both applications shifted from technology to learning, from theory to practice, and from technology to cognition, with the latter serving as the key mechanism linking immersive environments to learning outcomes. Immersion, motivation, and interaction are benefits of using these technologies. However, the technology’s impact on learning depends on the quality of instructional design and the depth of cognitive processing it elicits. The study incorporates ideas from constructivist learning theory, cognitive load theory, and self-determination theory, suggesting a cognitive-engagement-based approach to immersive learning in higher education. The review helps advance theory by clarifying the role of cognitive engagement as a mediating construct and offers practical implications for creating effective immersive learning environments.
Ahmed, T., Kobir, M. H., Yang, Y., Olsen, A. A., Fuad, M., & Deb, S. (2026). Evaluating the efficacy of virtual reality-based training in classroom settings for additive manufacturing education. Displays, 91, 103257. https://doi.org/10.1016/j.displa.2025.103257
Alhalabi, M., Ghazal, M., Haneefa, F., Yousaf, J., & El-Baz, A. (2021). Smartphone handwritten circuits solver using augmented reality and capsule deep networks for engineering education. Education Sciences, 11(11), 661. https://doi.org/10.3390/educsci11110661
Alshehri, A. H. (2026). Engagement with AR-enhanced language learning: Linking digital innovation to national educational reform goals. Presence: Teleoperators and Virtual Environments, 35, 231–241. https://doi.org/10.1162/PRES.a.427
Asadi, S., Ardakani, M. K., Iranmanesh, M., Kropff, J., Ghobakhloo, M., Foroughi, B., & Babaee Tirkolaee, E. (2026). The role of hedonic quality stimulation, immersion, and privacy concerns in metaverse adoption: Evidence from higher education. Journal of Educational Computing Research. https://doi.org/10.1177/07356331261437560
Beketov, V., Lebedeva, M., & Taranova, M. (2024). The impact of VR and AR technologies on the academic achievements of medical students: The age aspect. Interactive Learning Environments, 32(10), 6451–6461. https://doi.org/10.1080/10494820.2023.2266460
Bodur, G., Turhan, Z., Altun, Y. E., Kilicaslan, K., Alikan, B., Özer, F., & Can, G. (2025). Evaluating the effectiveness of virtual reality simulation in CPR training for nursing students: A randomized controlled trial. Nurse Education in Practice, 87, 104486. https://doi.org/10.1016/j.nepr.2025.104486
Camilleri, C., Caruana, L. F., Pulé, S., Mora, C. E., & Camilleri, L. (2025). Investigating the factors influencing augmented reality adoption in blended learning environments for mechanical engineering students. International Journal of Information and Education Technology, 15(5), 912–921. https://doi.org/10.18178/ijiet.2025.15.5.2297
Chen, C.Y., Shi, X. W., Yin, S.Y., Fan, N.Y., Zhang, T.Y., Zhang, X.N., Yin, C.T., & Mi, W. (2024). Application of the online teaching model based on BOPPPS virtual simulation platform in preventive medicine undergraduate experiment. BMC Medical Education, 24, 1255. https://doi.org/10.1186/s12909-024-06175-7
Chen, J., Fu, Z., Liu, H., & Wang, J. (2023). Effectiveness of virtual reality on learning engagement: A meta-analysis. International Journal of Web-Based Learning and Teaching Technologies, 19(1), 1–14. https://doi.org/10.4018/IJWLTT.334849
Dewangan, N. K., & Chandrakar, P. (2024). Implementing blockchain and deep learning in the development of an educational digital twin. Soft Computing, 28, 6619–6636. https://doi.org/10.1007/s00500-023-09501-1
Generosi, A., Agostinelli, T., Ceccacci, S., Mengoni, M., & others. (2022). A novel platform to enable the future human-centered factory. International Journal of Advanced Manufacturing Technology, 122, 4221–4233. https://doi.org/10.1007/s00170-022-09880-z
Giussani, R., Dozio, N., Becattini, N., Cascini, G., Ferrise, F., & Morosi, F. (2025). Study on the benefits of virtual reality as a support for STEM learning. Computer Applications in Engineering Education, 33(4), e70065. https://doi.org/10.1002/cae.70065
Hou, H. C., & Lan, H. (2026). Exploring students’ environmental preferences in classrooms: A VR-based discrete choice experiment. Building and Environment, 293, 114315. https://doi.org/10.1016/j.buildenv.2026.114315
Ibili, E., Ölmez, M., ?bili, A. B., Bilal, F., Cihan, A., & Okumu?, N. (2024). Assessing the effectiveness and student perceptions of synchronous online flipped learning supported by a metaverse-based platform. Education and Information Technologies, 29(14), 18643–18673. https://doi.org/10.1007/s10639-024-12542-0
Jing, C., Zhao, X., Ren, H., Chen, X., & Gaowa, N. (2022). An approach to oral English assessment based on intelligent computing model. Scientific Programming, 2022, 4663574. https://doi.org/10.1155/2022/4663574
Kiraly, R., Kiraly, S., & Palotai, M. (2024). Investigating usability of neural network teaching using AR/VR tools. Education and Information Technologies, 29(10), 13085–13104. https://doi.org/10.1007/s10639-023-12349-5
Liang, Y., & Hu, G. (2026). Investigating L2 listening comprehension in immersive VR. Computers and Education, 248, 105593. https://doi.org/10.1016/j.compedu.2026.105593
Liu, L.-A., & Hwang, G.-J. (2025). Peer assessment-facilitated SVVR cultural learning. Presence: Teleoperators and Virtual Environments, 34, 1–26. https://doi.org/10.1162/PRES.a.406
Luria, E., Rothgangel, M., & Gross, Z. (2025). VR and emotional engagement in Holocaust education. Educational Media International, 62(3), 380–404. https://doi.org/10.1080/09523987.2025.2490914
Mojsoska, B., Pande, P., Moeller, M. E., Ramasamy, P., & Jepsen, P. M. (2024). VR in organic chemistry education. Journal of Chemical Education, 101(11), 4686–4693. https://doi.org/10.1021/acs.jchemed.4c00099
Nuthanapati, A. K., Cherukuri, K., & Dukkipati, N. R. (2022). Education process re-engineering through spectral pyramid framework. Journal of Engineering Education Transformations, 35(Special Issue 1), 81–86. https://doi.org/10.16920/jeet/2022/v35is1/22012
Predescu, S.L., Caramihai, S. I., & Moisescu, M.A. (2023). Impact of VR application in academic context. Applied Sciences, 13(8), 4748. https://doi.org/10.3390/app13084748
Shiradkar, S., Rabelo, L., Alasim, F., & Nagadi, K. (2021). Virtual world as an interactive safety training platform. Information, 12(6), 219. https://doi.org/10.3390/info12060219
Shu, X., & Gu, X. (2023). Smart education model enabled by Edu-metaverse. Systems, 11(2), 75. https://doi.org/10.3390/systems11020075
Sun, H. (2023). VR and game-based English learning using fuzzy deep model. Computer-Aided Design and Applications, 20(S14), 231–248. https://doi.org/10.14733/cadaps.2023.S14.231-248
Tan, S., Liu, Y., & Wang, L. (2026). AI content generation-enabled virtual museums. Applied System Innovation, 9(3), 64. https://doi.org/10.3390/asi9030064
Tasnim, N., & Baek, J.-H. (2023). Dynamic edge convolutional neural network for action recognition. Sensors, 23(2), 778. https://doi.org/10.3390/s23020778
Tao, E., & Jiang, H. (2024). Virtual simulation platform for ideological education. Applied Mathematics and Nonlinear Sciences, 9(1), 963. https://doi.org/10.2478/amns.2023.2.00963
Wang, W.-S., Lin, C.-J., Lee, H.-Y., Huang, Y.-M., & Wu, T.-T. (2025). ChatGPT integration in VR experiential learning. Interactive Learning Environments, 33(2), 1770–1787. https://doi.org/10.1080/10494820.2024.2375644
Wang, Y., & Bao, X. (2026). AI-driven business English education enhancement mechanism. Ingegneria Sismica, 43(2). https://doi.org/10.65102/is2026645
Wang, Y. (2025). AI-driven personalized recommendation system for digital media art education. International Journal of Gaming and Computer-Mediated Simulations, 17(1). https://doi.org/10.4018/IJGCMS.396267
Yin, X., Zhang, J., Li, G., & Luo, H. (2024). Learner satisfaction in virtual learning environments. Electronics, 13(12), 2277. https://doi.org/10.3390/electronics13122277
Yuki, L. K., Anoegrajekti, N. (2026). SVVR flipped classroom and engagement in writing skills. International Journal of Learning, Teaching and Educational Research, 25(4), 475–493. https://doi.org/10.26803/ijlter.25.4.22
Zhai, H. (2023). VR-enabled deep learning for English teaching via webcast. Computer-Aided Design and Applications, 20(S14), 150–167. https://doi.org/10.14733/cadaps.2023.S14.150-167
Akbar, W., Akmal, S., Abdullasim, N., Mubeen, M., & Bakr, H. A. (2026). Cognitive Engagement in Immersive Learning Environments: A Narrative Review and Proposed Conceptual Framework for Higher Education. International Journal of Academic Research in Progressive Education and Development, 15(3), 1801–1817.
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