The Impact of Virtual Reality on Cognitive Load Among Senior Students at Middle Technical University: An Empirical Study

Saif M Duhaim

doi:10.47134/jtsi.v3i2.5930

Authors

Saif M Duhaim Baghdad Middle Technical University

DOI:

https://doi.org/10.47134/jtsi.v3i2.5930

Keywords:

Virtual Reality, Cognitive Load Theory, Immersive Learning, Middle Technical University, NASA-TLX, Head-Mounted Display, Higher Education Iraq, Learning Performance, Presence, Structural Equation Modeling

Abstract

The adoption of Virtual Reality (VR) in higher education has gained increasing worldwide interest, however, its evaluation as an effect on workload and cognitive-load related learning outcomes for senior technical university students in Iraq is still an unaddressed issue. This study sought to fill the gap in the literature by investigating the effect of a VR-based instruction on the Nasa TlX workload indicators concerning the cognitive load, the effect of the presence and the intrinsic motivation on the learning performance of senior engineering students in a technical university in Baghdad. Employing a quasi-experimental pre-post control group design, 80 learners participated and were randomly assigned to either a VR group (n = 40) who experienced the interactive content through Meta Quest 2 HMDs or a control group (n = 40) who were taught in a traditional lecture style. The cognitive workload was assessed by NASA-TLX, and the analyses were performed with the use of independent-samples t-tests, MANOVA and exploratory Structural Equation modeling (SEM). Results showed that the VR group had significantly lower mental demand (M = 52.4vs. 61.7, p = .001) and frustration (M = 30.4vs. 44.8, p < .001), but the overall NASA-TLX workload index was not significantly different between the two groups (M = 49.65vs. 52.17, p = .184). The VR group outperformed in learning (MCQ: M = 23.4/30 vs. 19.7/30, d = 1.00), knowledge retention at one-week post-test (78.6% vs. 62.4%, d = 1.53), and intrinsic motivation scores. . Exploratory SEM analysis showed that the immersion in VR could promote learning indirectly by decreasing the extraneous-load-related workload (β = −.54) and enhancing presence (β = . 71). These results suggest that the VR-based intervention has the potential to improve certain aspects of the workload and learning outcomes in higher education in developing countries, although statements regarding an overall reduction in cognitive load should be considered with caution.

References

Al-Khiami, A. (2024). Enhancing concrete structures education: Impact of virtual reality on motivation, performance and usability for undergraduate engineering students. Journal of Computer Assisted Learning, 40(1), 306–325. https://doi.org/10.1111/jcal.12881

Betts, K., Reddy, P., Galoyan, T., Delaney, B., McEachron, D. L., Izzetoglu, K., & Shewokis, P. A. (2023). An examination of the effects of virtual reality training on spatial visualization and transfer of learning. Brain Sciences, 13(6), 890. https://doi.org/10.3390/brainsci13060890

Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. https://doi.org/10.1207/s1532690xci0804_2

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146

Franklin, A. E., Thielke, L., Gilbert, G. E., & Waller, M. (2024). Psychometric testing of NASA-TLX to measure learners' cognitive load in individual and group nursing simulations. Clinical Simulation in Nursing. https://doi.org/10.1016/j.ecns.2024.00099

Han, J., Liu, G., & Zheng, Q. (2023). Prior knowledge as a moderator between signaling and learning performance in immersive virtual reality laboratories. Frontiers in Psychology, 14, 1118174. https://doi.org/10.3389/fpsyg.2023.1118174

Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human Mental Workload (pp. 139–183). North-Holland. DOI tidak tersedia.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Islam, F., Bright, Z., Zhan, L., & Shi, C. (2026). An experimental exploration of cognitive workload and situational awareness in virtual reality: Implications for non-clinical emotional support. Mental Health Research, e70061. https://doi.org/10.1002/mpr.70061

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

Johnson-Glenberg, M. C. (2019). The necessary nine: Design principles for embodied VR and active STEM education. In P. Díaz, A. Ioannou, K. K. Bhagat, & J. M. Spector (Eds.), Learning in a Digital World (pp. 83–112). Springer. DOI tidak tersedia.

Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need? Educational Psychology Review, 23(1), 1–19. https://doi.org/10.1007/s10648-010-9150-7

Ki, S., Park, S., Ryu, J., Kim, J., & Kim, I. (2024). Alone but not isolated: Social presence and cognitive load in learning with 360 virtual reality videos. Frontiers in Psychology, 15, 1305477. https://doi.org/10.3389/fpsyg.2024.1305477

Lessiter, J., Freeman, J., Keogh, E., & Davidoff, J. (2001). A cross-media presence questionnaire: The ITC-Sense of Presence Inventory. Presence: Teleoperators and Virtual Environments, 10(3), 282–297. DOI tidak tersedia.

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., & Mayer, R. E. (2022). Benefits of taking a virtual field trip in immersive virtual reality: Evidence for the immersion principle in multimedia learning. Educational Psychology Review, 34(3), 1771–1798. https://doi.org/10.1007/s10648-022-09675-4

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

Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225–236. https://doi.org/10.1016/j.learninstruc.2017.12.007

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. https://doi.org/10.1207/S15326985EP3801_6

Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. https://doi.org/10.1207/S15326985EP3801_1

Parong, J., & Mayer, R. E. (2018). Learning science in immersive virtual reality. Journal of Educational Psychology, 110(6), 785–797. https://doi.org/10.1037/edu0000241

Ryan, R. M. (1982). Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. Journal of Personality and Social Psychology, 43(3), 450–461. DOI tidak tersedia.

Slater, M., & Wilbur, S. (1997). A framework for immersive virtual environments (FIVE): Speculations on the role of presence in virtual environments. Presence: Teleoperators and Virtual Environments, 6(6), 603–616. DOI tidak tersedia.

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4

Sweller, J. (2010). Element interactivity and intrinsic, extraneous, and germane cognitive load. Educational Psychology Review, 22(2), 123–138. https://doi.org/10.1007/s10648-010-9128-5

Sweller, J. (2011). Cognitive load theory. In J. P. Mestre & B. H. Ross (Eds.), The Psychology of Learning and Motivation (Vol. 55, pp. 37–76). Academic Press. DOI tidak tersedia.

van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147–177. https://doi.org/10.1007/s10648-005-3951-0

Wu, B., Yu, X., & Gu, X. (2020). Effectiveness of immersive virtual reality using head-mounted displays on learning performance: A meta-analysis. British Journal of Educational Technology, 51(6), 1991–2005. https://doi.org/10.1111/bjet.13023