Balancing human and AI instruction: insights from secondary student satisfaction with AI-assisted learning

AI-assisted learning is gaining recognition for its potential to enhance educational outcomes, yet its impact on student satisfaction, particularly in the context of programming courses, has not been thoroughly investigated. This study aimed to fill this gap by assessing satisfaction among 70 secondary students through a three-week AI-assisted project as part of their programming course. The results revealed a generally positive reception, with satisfaction levels consistent across genders, grades, and experiences with AI-assisted learning. Notably, a robust positive correlation was observed between satisfaction with human instructors and other components of the learning experience. In contrast, the learning sequence was found to have a counterintuitive negative correlation with overall satisfaction. Building on these insights, we developed a conceptual framework that delineates the factors determining student satisfaction in AI-assisted learning environments. Our findings underscore the need for a balanced approach that incorporates both AI technology and human interaction in educational settings.