Empowered by AI: Investigating the Role of AI Tools in Fostering Self-Directed Learning and Motivation among TVET Students

Abstract

The rapid integration of artificial intelligence (AI) tools in higher education has extended beyond task assistance to influencing students’ learning behaviours and motivation. In Technical and Vocational Education and Training (TVET), where independent problem-solving and technical competence are essential, understanding the developmental role of AI tools is increasingly important. This study investigates how AI tools contribute to self-directed learning and learning motivation among TVET students. A qualitative case study design was employed involving ten Semester 5 Information Technology students in a Malaysian polytechnic. Data were collected through semi-structured interviews, reflective journals, and document analysis. Thematic analysis revealed two overarching themes. First, AI tools strengthened self-directed learning processes, particularly in planning, monitoring, and autonomous task execution. Second, AI usage enhanced students’ motivational states, including increased confidence, greater persistence, and reduced anxiety during technical challenges. While minor risks of over-reliance exist, students demonstrated controlled AI usage. Findings suggest AI functions as a developmental enabler in TVET learning environments.

Keywords: Artificial intelligence; Self-directed learning; Motivation; TVET; Qualitative research