Conditional Optimism and Contextual Factors in Academic Staff Adoption of AR/VR for Student Assessment
DOI:
https://doi.org/10.14689/enad.44.2235Keywords:
Student assessment, higher education, augmented reality, virtual reality, technology adoption, conditional optimismAbstract
The integration of augmented reality (AR) and virtual reality (VR) technologies is rapidly transforming educational environments, yet their application in student assessment remains underexplored, particularly within higher education. This study investigates the intentions and determinants influencing academic staff’s adoption of AR and VR for student assessment in Turkish universities, drawing on the Theory of Planned Behavior (TPB) and supplementary technology acceptance frameworks. Employing a qualitative research design, semi-structured interviews were conducted with 30 academic staff members representing diverse disciplines and levels of experience. Thematic analysis revealed that attitudes, subjective norms, and perceived behavioral control are foundational predictors of adoption intention; however, their influence is substantially mediated by contextual factors such as institutional readiness, innovation climate, and a newly identified construct conditional optimism. Findings highlight the necessity of robust infrastructure, targeted professional development, and supportive organizational culture for successful AR/VR integration. The study proposes theoretical and practical insights for policymakers, institutional leaders, and technology developers. This research advances understanding of technology adoption in educational assessment and provides a roadmap for future studies and implementation strategies.
References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. (2006, January). Constructing a theory of planned behavior questionnaire. University of Massachusetts Amherst. https://people.umass.edu/aizen/pdf/tpb.measurement.pdf
Akçayır, M., & Akçayır, G. (2017). Advantages and challenges associated with augmented reality for education: A systematic review of the literature. Educational Research Review, 20, 1–11. https://doi.org/10.1016/j.edurev.2016.11.002
Al-Emran, M., Al-Qaysi, N., Al-Sharafi, M. A., Alhadawi, H. S., Ansari, H., Arpaci, I., & Ali, N. A. (2025). Factors shaping physicians’ adoption of telemedicine: A systematic review, proposed framework, and future research agenda. International Journal of Human–Computer Interaction, 41(13), 8495–8514. https://doi.org/10.1080/10447318.2024.2410536
Amirbekova, E., Shertayeva, N., & Mironova, E. (2024). Teaching chemistry in the metaverse: The effectiveness of using virtual and augmented reality for visualization. Frontiers in Education, 8, 1184768. https://doi.org/10.3389/feduc.2023.1184768
Ateş, H., & Garzón, J. (2022). Drivers of teachers’ intentions to use mobile applications to teach science. Education and Information Technologies, 27(2), 2521–2542. https://doi.org/10.1007/s10639-021-10671-4
Ateş, H., & Garzón, J. (2023). An integrated model for examining teachers’ intentions to use augmented reality in science courses. Education and Information Technologies, 28(2), 1299–1321. https://doi.org/10.1007/s10639-022-11239-6
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dwivedi, S., & Vig, S. (2024). Blockchain adoption in higher-education institutions in India: Identifying the main challenges. Cogent Education, 11(1), 2292887. https://doi.org/10.1080/2331186X.2023.2292887
Hofstede, G. (2001). Culture’s consequences: Comparing values, behaviors, institutions and organizations across nations (2nd ed.). Sage.
Jensen, L., & Konradsen, F. (2018). A review of the use of virtual reality head-mounted displays in education and training. Education and Information Technologies, 23(4), 1515–1529. https://doi.org/10.1007/s10639-017-9676-0
Lee, T., Wen, Y., Chan, M. Y., Azam, A. B., Looi, C. K., Taib, S., … Cai, Y. (2024). Investigation of virtual & augmented reality classroom learning environments in university STEM education. Interactive Learning Environments, 32(6), 2617–2632. https://doi.org/10.1080/10494820.2022.2155838
Moro, C., Birt, J., Stromberga, Z., Phelps, C., Clark, J., Glasziou, P., & Scott, A. M. (2021). Virtual and augmented reality enhancements to medical and science student physiology and anatomy test performance: A systematic review and meta-analysis. Anatomical Sciences Education, 14(3), 368–376. https://doi.org/10.1002/ase.2049
Moustakas, C. (1994). Phenomenological research methods. Sage.
Parmaxi, A., & Demetriou, A. A. (2020). Augmented reality in language learning: A state-of-the-art review of 2014–2019. Journal of Computer Assisted Learning, 36(6), 861–875. https://doi.org/10.1111/jcal.12486
Prikshat, V., Kumar, S., Patel, P., & Varma, A. (2025). Impact of organisational facilitators and perceived HR effectiveness on acceptance of AI-augmented HRM: An integrated TAM and TPB perspective. Personnel Review, 54(3), 879–912.
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
Riyanti, I., Copriady, J., & Linda, R. (2022). Student needs analysis for the development of augmented reality integrated e-modules about particles in science learning. Unnes Science Education Journal, 11(2), 115–122. https://doi.org/10.15294/usej.v11i2.58309
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
Schmidt, E., & Cohen, J. (2013). The new digital age: Reshaping the future of people, nations and business. Knopf.
Schouten, D., Nicoletti, G., Dille, B., Chia, C., Vendittelli, P., Schuurmans, M., … Khalili, N. (2025). Navigating the landscape of multimodal AI in medicine: A scoping review on technical challenges and clinical applications. Medical Image Analysis, 105, 103621. https://doi.org/10.1016/j.media.2025.103621
Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of Educational Research, 79(2), 625–649. https://doi.org/10.3102/0034654308325896
Trowler, P. (1998). Academics responding to change: New higher education frameworks and academic cultures. Society for Research into Higher Education & Open University Press.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Vola, E., Stoltz, R., & Schumpert, C. A. (2025). Impacts of virtual reality experiences: Enhanced undergraduate student performance and engagement with use of 360-degree video. Virtual Worlds, 4(2), 14. https://doi.org/10.3390/virtualworlds4020014
Xuan, H., Liu, Q., & Wang, L. (2024). The impact of incentive policies on shipowners’ adoption behavior of clean energy technologies: Evidence from China. Marine Policy, 167, 106277. https://doi.org/10.1016/j.marpol.2024.106277
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