Abstract

Personalizing adult learner experiences have been shown to improve engagement, satisfaction, and academic performance. Artificial Intelligence (AI) is widely used for personalization; however, question remains about its effective integration into higher education teaching practice. This paper presents a comparative analysis of two case studies examining AI-based personalization using academagogy, a learner-centered teaching model. We analyzed learner data obtained from interactions with a learning management system, self-reflections, and semi-structured interviews. The findings indicate enhancement in behavioral, emotional, and cognitive engagement. Additionally, the comparison revealed mixed results in final grades, revealing a pattern of ghost learners who were enrolled but did not engage in active learning. These findings highlight the complex challenges faced by adult learners and provide recommendations for integrating AI into tertiary education to inform decision-making, benefiting educators and adult learners.

Download

Share

COinS