The Dual Impact of Artificial Intelligence on Students' Autonomous Learning: A Self-Determination Theory Perspective
TL;DR
It is argued that AI itself is neither entirely beneficial nor harmful, and its impact largely depends on how students use AI and how educators integrate it into learning environments.
Abstract
Artificial intelligence (AI), especially generative AI tools such as ChatGPT, has rapidly transformed modern education and students' learning behaviors. While AI provides students with convenient access to information, personalized feedback, and flexible learning support, its influence on students' autonomous learning in higher education remains controversial. Drawing on Self-Regulated Learning and Self-Determination Theory, this paper presents a theoretical analysis of the dual effects of AI on students' autonomous learning. Existing literature suggests that AI can strengthen self-directed learning, improve learning efficiency, and increase access to educational resources. However, excessive dependence on AI may weaken critical thinking, reduce independent problem-solving, and diminish meaningful interaction between students and teachers. This paper argues that AI itself is neither entirely beneficial nor harmful. Instead, its impact largely depends on how students use AI and how educators integrate it into learning environments. When AI supports rather than replaces thinking, it can enhance autonomous learning. Otherwise, it may encourage passive dependence. The paper also suggests ways to use AI responsibly, so that it supports learning without taking it over.