Esti Schwartz, Ina Blau E83 Caspi, 2010). All items were rated on a six-point Likert scale (1 = strongly disagree, 6 = strongly agree) . Construct Validation A confirmatory factor analysis (CFA) supported the four-factor structure. One emotional item (QE2) was removed due to low loading. The revised model showed acceptable fit: χ²/df = 1.77, RMSEA = .056, SRMR = .08, with CFI (.893) and TLI (.866) approaching the .90 threshold. Composite scores were then calculated using the retained items. Reliability was acceptable across all scales (α = .73–.86). Procedure and Analysis Lessons were delivered in authentic classroom settings, and students completed questionnaires immediately afterward. A two-way MANCOVA examined the effects of technology type and age on perceived learning, controlling for teacher experience. Significant multivariate results were followed by univariate ANCOVAs and Bonferroni-adjusted comparisons. The study received ethical approval from the Israel Ministry of Education Chief Scientist Office and the participating institutions. Findings and Discussion Preliminary Analyses Preliminary analyses examined whether background variables influenced students' learning perceptions. A MANOVA test with age as a fixed factor and teacher experience as a covariate revealed significant multivariate effects for both variables, as well as a significant interaction. Univariate tests showed that age and teacher experience affected all four learning outcomes. Because both contributed meaningfully to variability in students' perceptions, age was retained as a factor and teacher experience as a covariate in subsequent analyses. Main Analysis: Effects of Immersive Technology A two-way MANCOVA was conducted to examine the effects of immersive technology type (Desktop VR, Immersive Rooms, fully immersive VR) and student age on perceived immersion, and on cognitive, emotional, and social learning, controlling for teacher experience. The analysis revealed a significant multivariate main effect of technology, indicating that the immersive format meaningfully shaped students' learning perceptions. Significant multivariate effects were also found for age and for the Technology × Age interaction, demonstrating that technology effects varied across developmental stages. Follow-up univariate ANCOVAs showed that technology significantly affected all four learning dimensions. The largest effects emerged for immersion and cognitive learning, suggesting that differences between technologies were most pronounced in how present students felt in the environment and how effectively they perceived they learned from it. Estimated marginal means (Table 1) indicated that Desktop VR (DVR) consistently produced the highest scores across all domains, outperforming Immersive Rooms (IR) and, in some cases, fully immersive VR (VR). IR showed the lowest ratings overall, suggesting that this medium-immersion environment may not provide the interactional or cognitive support necessary for strong learning perceptions. Table 1 presents the estimated marginal means and Bonferroni comparisons for each learning outcome across the three technology types and age groups.
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