CONNECT: An AI-Powered Solution for Student Authentication and Engagement in Cross-Cultural Digital Learning Environments

Abstract

The COVID-19 pandemic accelerated the shift to digital education as universities across the world rapidly adopted virtual classrooms for remote learning. Ensuring continuous student engagement in virtual environments remains one of the key challenges. This paper discusses how AI and data analytics are being applied to education, particularly the ways in which technologies such as biometrics and facial recognition can be used to improve student engagement in online and hybrid learning environments. This paper tries to revisit the dynamics of engagement across virtual platforms by comparing traditional learning models and digital learning models and showing the gaps that exist. This study reviewed six widely used video conferencing tools and their effectiveness in fostering engagement in virtual classrooms. The research goes on to investigate cross-cultural tech adoption in education—how regions and educational systems respond to these emerging technologies. Against this background of the challenges identified, a new application, “CONNECT”, is proposed in this paper that can integrate AI-driven features on face recognition and speech-to-text and attendance monitoring to enable real-time authentication and tracking of engagement. This study also provides an overview of the theoretical models of digital, hybrid, and blended learning and provides actionable recommendations for future research and innovation in cross-cultural online education.