AI-ENHANCED MIXED REALITY IN EDUCATION: A SYSTEMATIC ANALYSIS OF IMMERSIVE LEARNING TECHNOLOGIES AND STUDENT DEVELOPMENT OUTCOMES
Keywords:
AI-Enhanced Mixed Reality, Immersive Learning, Educational Technology Integration, Adaptive Learning Systems, Digital PedagogyAbstract
The integration of Artificial Intelligence (AI) with Mixed Reality (MR) technologies represents a significant advancement in educational technology, offering unprecedented opportunities for personalized and immersive learning experiences. This article examines the implementation and effectiveness of AI-enhanced MR systems across diverse educational settings (n=245) through a mixed-methods approach, incorporating quantitative analysis of student performance metrics and qualitative assessment of learner engagement. The findings demonstrate a statistically significant improvement in student learning outcomes (p < 0.001) when utilizing AI-enhanced MR, with particular effectiveness in STEM subjects showing a 27% increase in conceptual understanding compared to traditional methods. The article identifies key success factors including adaptive learning algorithms, real-time feedback mechanisms, and immersive visualization capabilities, while also addressing critical challenges such as infrastructure requirements, accessibility concerns, and pedagogical integration. Analysis of longitudinal data collected over two academic years reveals sustained improvements in student engagement (Cohen's d = 0.82) and knowledge retention (Cohen's d = 0.76). Furthermore, the article presents a novel framework for implementing AI-enhanced MR in educational institutions, incorporating considerations for scalability, data privacy, and teacher professional development. These findings have significant implications for educational policy, pedagogical practice, and the future development of immersive learning technologies in increasingly digitized educational environments.
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