Integrating AI Into Online Engagement Models for Engineering Education: A Comprehensive Review

Abstract

In the present era, where online learning has taken the spotlight in higher education, especially in engineering education, student engagement remains a critical determinant of academic success. Online engagement models that structure strategies to captivate and sustain students’ involvement in virtual learning environments play a vital role in addressing the unique challenges of remote education. This comprehensive review examines the potential of Artificial Intelligence (AI) to revolutionise these models in the context of engineering education. The study identifies how AI tools, such as adaptive learning systems and intelligent tutoring systems, can enhance personalisation, provide real-time feedback, and create interactive learning experiences by analysing literature from leading academic databases over the last decade. The review also discusses the broader implications of AI integration, considering both opportunities and challenges for educators and institutions. Limitations and future research directions are identified, including the need for cross-cultural validations, longitudinal studies, and the extension of these findings to other fields of education. This research adds to the expanding corpus of literature on student engagement, offering a unique perspective on the intersection of AI and online student engagement by guiding engineering educators in creating a more effective, inclusive, and adaptive virtual learning environment.