A Systematic Literature Review of Self-regulated Learning and Artificial Intelligence in Higher Education

Abstract

Research highlights a pressing need for conceptualizing Self-Regulated Learning (SRL) in modern higher education, particularly in the context of Artificial Intelligence (AI). We systematically review studies on SRL and AI in higher education. A total of 934 articles were found on the Web of Science or WoS (877) and Scopus (57) and assessed using PRISMA protocol. A total of 14 studies were included in this review. The systematic review seeks to examine and synthesize: aspects of SRL that have been studied at the intersection of AI and SRL, limitations reported by the studies at the intersection of AI and SRL, and considerations for a new model of SRL in light of AI. Findings reveal diverse theories and technologies used and attributed to SRL building with AI in higher education literature. Such diversity can lead to a lack of a universal outlook and generalizable findings. The discussion highlights avenues for future research and proposes methodological approaches for studying SRL in AI-enabled learning environments. This work contributes to a set of practices and tools to better conceptualize SRL with AI.