Esti Schwartz, Ina Blau E85 Technology effects differed across age groups (Table 2). Among younger students, DVR and VR produced substantially higher immersion and cognitive scores compared with IR. For middle-school students, all three technologies performed more similarly, although IR remained lower overall. Among older students, differences between technologies narrowed further. These patterns suggest that technology-related learning perceptions depend not only on immersion level but also on developmental readiness. Overall, the findings indicate that DVR offers the most favorable balance of immersion, usability, and instructional clarity, supporting perceived learning more effectively than either immersive rooms or fully immersive VR. Taken together, these patterns suggest that effective use of immersive technologies depends on aligning immersion level with learners' cognitive readiness and classroom interaction needs. Educators should therefore prioritize formats that maintain communication, provide clear guidance, and support sustained engagement. References Ausejo, E. S. (2025). Exploring Teachers' Views on Using Immersive Virtual Reality for Teaching History. Digital Education Review, (47), 109-126. https://doi.org/10.1344/der.2025.47.108-126 Blau, I., & Caspi, A. (2010). Media naturalness, visual anonymity, and learning: Comparing face-toface and audio conferencing instruction. In N. Kock (Ed.), Evolutionary psychology and information systems research: A new approach to studying the effects of modern technologies on human behavior (pp. 193-216). Springer, Boston, MA. http://dx.doi.org/10.1007/978-1-4419-6139-6 Crogman, H. T., Cano, V. D., Pacheco, E., Sonawane, R. B., & Boroon, R. (2025). Virtual reality, augmented reality, and mixed reality in experiential learning: Transforming educational paradigms. Education Sciences, 15(3), 303. https://doi.org/10.3390/educsci15030303 Makransky, G., & Lilleholt, L. (2018). A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educational Technology Research and Development, 66(5), 1141–1164. https://doi.org/10.1007/s11423-018-9581-2 Makransky, G., & Petersen, G. B. (2021). The cognitive affective model of immersive learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educational psychology review, 33(3), 937-958. https://doi.org/10.1007/s10648-020-09586-2 Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenannt, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778 Selzer, M. N., & Castro, S. M. (2023). A methodology for generating virtual reality immersion metrics based on system variables. Journal of Computer Science & Technology, 23. https://doi.org/10.24215/16666038.23.e08
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