Assessing the Impact of Immersive Technologies on Academic Performance, Cognitive Load, Engagement, and Self‐Regulated Learning: A Quasi‐Experimental Study in Kazakhstan

Background The relevance of this study stems from the digital transformation of Kazakhstan's higher education system and the need for pedagogically sound immersive technologies: virtual ( VR ) and augmented realities ( AR ), capable of improving the quality of education under conditions of limited educational resources. Objectives This quasi‐experimental study aims to assess the impact of VR/AR technologies on the academic achievement and psychological characteristics (i.e., cognitive load, engagement, and self‐regulated learning strategies) of students pursuing a degree in pedagogy, psychology, engineering, and technology at universities in Kazakhstan. Methods This study used a quasi‐experimental design with control and experimental groups and conducted pre‐ and pos t ‐tests to assess the effect of the intervention. The study also used a cognitive load scale and qualitative interviews. Results and Conclusions Results showed a significant increase in academic performance in the VR/AR group (Δ = +22.7%–24.4%; Cohen's d = 1.54–1.78; p < 0.001) as compared to the control group ( d ≈0.8–0.9). The overall cognitive load did not increase, but scores for performance (81.5 vs. 73.8; p < 0.001), effort (69.2 vs. 60.7; p < 0.001), and frustration (25.3 vs. 28.9; p = 0.032) were higher. Statistically significant differences were found within the VR/AR group in terms of engagement and self‐regulated learning strategies ( p < 0.001). A positive correlation was found between engagement and self‐regulation ( r = 0.62), whereas a negative correlation was present between engagement and cognitive load ( r = −0.28…−0.31). VR/AR usage had a significant moderating effect (η 2 ≈0.39–0.42), whereas the moderation effect of university affiliation was insignificant. The proposed conceptual framework has demonstrated its empirical applicability in this study. The results obtained, taking contextual limitations into account, can serve as an empirical basis for the future implementation of virtual and augmented reality solutions.