Using AI and learning analytics to enhance student engagement in hybrid learning

Hybrid learning, which combines face-to-face and online instruction, has become a prevalent educational model, yet it faces challenges in maintaining student engagement. The disconnect between online and in-person components often leads to decreased participation and lower academic performance. This study explores the integration of AI and learning analytics to enhance student engagement in hybrid learning environments. The design features dual learning modes, an interactive display, and AI-driven personalization to create a cohesive and interactive experience. By providing real-time engagement metrics, personalized learning paths, and dynamic feedback, the design addresses the shortcomings of traditional hybrid models. Targeted at educational institutions and technology companies, this innovative approach aims to improve academic outcomes, reduce dropout rates, and ensure equitable access to education. Its potential for commercial success is significant, given the growing demand for advanced educational technologies. The design's seamless integration of AI and learning analytics offers a promising solution to the challenges faced in hybrid learning, making it a valuable contribution to educational technology.