Personalized Learning in the Age of AI: A Case for Interest-Driven Education

The increasing disengagement of students in traditional education, understood as focused almostexclusively on the transmission of knowledge, highlights the need for more inclusive and personalizedlearning strategies. Interest plays a crucial role in this personalization, integrating cognitive, emotional,and evaluative aspects into the learning process. This qualitative study, framed within aphenomenological paradigm and a case study design, examines the implementation of AI-assistedpersonalized learning pathways to enhance interest in psychology students. Using the CHAEAquestionnaire, students’ learning styles and educational needs were identified, guiding the developmentof AI-supported learning pathways. Participants documented their experiences through field journals andfollow-up interviews. Findings indicate that interest evolves through sustained engagement, intrinsiccuriosity, knowledge integration, and personal relevance. AI-assisted personalization fostered motivationand self-efficacy, enhancing professional preparation. While promising, further research is needed toassess the long-term sustainability of interest development and its transferability to diverse educationalcontexts. Received: 06 October 2025 / Accepted: 22 February 2026 / Published: March 2026