AI and IoT in Education: Enhancing Classroom Interactivity and Student Engagement
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Abstract
This study examines how the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) can enhance classroom interactivity and student engagement in technology-supported educational environments. Using a systematic literature review guided by PRISMA procedures, the study analyses 67 peer-reviewed publications drawn from major academic databases including Scopus, Web of Science, IEEE Xplore, and Google Scholar. The review synthesises existing research on the pedagogical applications of AI-driven adaptive learning systems and IoT-enabled smart classroom technologies. The findings indicate that AI technologies, particularly intelligent tutoring systems and adaptive learning platforms, enable personalised learning pathways by analysing student performance data and providing real-time feedback. At the same time, IoT-enabled devices such as smart boards, wearable sensors, and connected classroom systems support interactive and data-driven learning environments. When integrated effectively, these technologies contribute to improved classroom interaction, increased student motivation, and more responsive instructional practices.
However, the review also identifies significant challenges associated with AI–IoT integration, including digital inequality, infrastructural limitations, data privacy concerns, and algorithmic bias. Addressing these issues requires coordinated efforts among educators, policymakers, and technology developers to ensure equitable and ethical implementation. By synthesising current research and identifying emerging trends, this study contributes to the growing body of scholarship on intelligent educational technologies and provides insights for designing more inclusive and interactive learning environments.
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