Learning in hybrid times: Comparing student experiences in traditional and GenAI-supported instruction

The emergence of generative artificial intelligence (GenAI) tools, such as ChatGPT, is reshaping the landscape of higher education by introducing new opportunities for learner autonomy, flexibility, and engagement. While extensive research has explored GenAI's technical capabilities and ethical implications, limited attention has been paid to students’ subjective learning experiences with AI-supported instruction. This study investigates how undergraduate students perceive and experience two instructional modes in a database management course: traditional lecturer-led instruction and GenAI-supported self-regulated learning. Sixty-eight second-year engineering students participated in the study, providing qualitative insights through open-ended survey responses. The findings reveal key cognitive, emotional, and strategic differences between the two approaches: traditional instruction fostered structure, immediate feedback, and emotional reassurance, while GenAI-supported learning promoted autonomy and exploration but raised concerns regarding reliability and critical thinking. Importantly, students did not view these modes as mutually exclusive, but rather as complementary components of a broader “learning puzzle,” balancing the stability of face-to-face instruction with the adaptability of GenAI to support diverse learning needs. This study contributes to a deeper understanding of hybrid learning environments and underscores the importance of nuanced, learner-centered integration of AI technologies in higher education.