A Review of the Impact of Generative Artificial Intelligence on Students' Learning Motivation

Abstract

The application of generative artificial intelligence (GenAI) in higher education has expanded rapidly, exerting a significant influence on multiple core dimensions of university students' learning. Based on the core framework of Self-Determination Theory (SDT), this study systematically reviews existing literature on the impact of GenAI on students' learning motivation. The findings suggest that GenAI can, to a certain extent, satisfy university students' basic psychological needs for autonomy and competence by providing personalized learning support, immediate feedback, and autonomous learning choices. It also promotes interaction among students and between students and learning content, thereby enhancing learning motivation. However, GenAI may also lead to excessive student dependence, the dissemination of inaccurate information, and a weakening of students' independent thinking abilities, thereby undermining their autonomy and perceived competence, and thus negatively affecting learning motivation. The study further highlights the need for scientific guidance and regulation regarding the use of GenAI in educational contexts.