Enhancing Students' Metacognition via AI-Driven Educational Support Systems
Yanan Yang, Nan Xia
Abstract
As the penetration of digital technology deepens and the demands for educational modernization grow, attention is increasingly being drawn towards the application of artificial intelligence (AI) in the field of education. Especially in educational practice, the optimization of students’ learning experiences and the enhancement of their metacognitive abilities through AI technology have captivated the interest of numerous educators and scholars. Metacognition, which represents a core skill in student self-regulation and self-management, has a significant impact on student learning outcomes and quality. However, current educational support systems primarily rely upon traditional methods of data collection and analysis, which have limitations in terms of real-time responsiveness, granularity, and comprehensiveness. The present research aims to investigate the integration of AI technology with a specific focus on the learning process through educational support systems and the development of a cooperative teaching interaction model. This will ultimately enhance the development of students’ metacognitive abilities more effectively.