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

The increasing disengagement of students in traditional education, understood as focused almost exclusively on the transmission of knowledge, highlights the need for more inclusive and personalized learning strategies. Interest plays a crucial role in this personalization, integrating cognitive, emotional, and evaluative aspects into the learning process. This qualitative study, framed within a phenomenological paradigm and a case study design, examines the implementation of AI-assisted personalized learning pathways to enhance interest in psychology students. Using the CHAEA questionnaire, students’ learning styles and educational needs were identified, guiding the development of AI-supported learning pathways. Participants documented their experiences through field journals and follow-up interviews. Findings indicate that interest evolves through sustained engagement, intrinsic curiosity, knowledge integration, and personal relevance. AI-assisted personalization fostered motivation and self-efficacy, enhancing professional preparation. While promising, further research is needed to assess the long-term sustainability of interest development and its transferability to diverse educational contexts.