Physical Learning Environments and AI-Powered Personalized Learning in Higher Education: A Systematic Literature Review

Abstract

In tightly managed tests, AI that gives each student a learning path tailored to them shows improvements of 0.42 to 0.76 standard deviations. However, this review of 22 studies (1984-2026) examines an overlooked aspect: the quality of the actual learning space. Barrett et al. (2015) found that classroom design explains 16% of the variation in student performance, about the same as the impact of the AI itself. We believe that temperature, noise, and lighting all make it harder for students to manage their own learning, and AI that adapts to students' needs requires self-direction to work

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