국내 AI 수학 학습 플랫폼의 적응형 학습에 대한 분석

Abstract

With the recent advancements in Artificial Intelligent (AI) technology, there‘s an emphasized need for adaptive and individualized education utilizing AI. Especially as the national approach to the development and implementation of AI digital textbooks, there exists a discrepancy in the shared understanding among researchers, policy makers, developers, implementers, and users regarding individualized and adaptive education. Such differences can potentially impact the efficiency of development and the effectiveness of implementation. Through a systematic literature review, this study identified the essential adaptive features required for AI-based mathematics digital textbooks and analyzed the current form of adaptive learning provided by Korea’s AI mathematics learning platforms. The analysis revealed that these platforms primarily focus on knowledge adaptivity, while aspects like emotional and motivational adaptivity or metacognivite adaptivity were less emphasized. In terms of how to adapt, our analysis indicates that the real-time monitoring for adjusting problem difficulty and individualized tasks data-based decision were not prominently showed. The findings suggest that researchers, policy makers, and developers need to collaboratively delve deeper into considering various adaptive strategies.