Meina Zhu, Annisa R. Sari
Given the increasing need for self-regulated learning (SRL) and the rapid advancement of artificial intelligence (AI), this study provides a systematic review of 25 selected empirical studies on the use of AI to support SRL. This study offers an overview of the state of AI use for SRL. The reviewed studies employed various AI technologies, such as chatbots, Intelligent Tutoring Systems, adaptive learning systems, e-books, and educational games, in different approaches and stages of SRL. However, the review also revealed limitations and concerns (e.g., inaccuracy, tracking behaviors, adaptability, AI literacy, and negative impact) regarding the use of AI to facilitate SRL. Based on the findings, we propose an AI-SRL conceptual framework comprising two layers: the learner layer (forethought, performance, self-reflection, and iteration) and the instructor layer (providing AI literacy, integrating AI into learning activities, offering continuous support, monitoring and measuring progress, and iterating for improvement). This framework represents an initial stage with potential for future development. © 2026 Elsevier Inc.
Learning Design and Technology & The Institute for AI and Data Science, Wayne State University, Detroit, MI, United States; Accounting Education Department, Yogyakarta State University, Yogyakarta, Indonesia
