Supporting Self-Regulated Learning by Affect Detection and Responding in AI-driven Learning Systems

Abstract

Emotions play a vital role in self-regulated learning (SRL)processes and drastically influence cognitive functioning.Along with creating individualized, engaging, flexible and inclusive learning environments, Artificial intelligence (AI) learning systems, especially intelligent tutoring systems (ITSs) have the potential to sense affective states of a learner and respond to them to maintain learning flow. This paper discusses the concept of AI in education (AIEd) followed by the explanation of the role of emotions in SRL. Highlighting theoretical and technical aspects, it provides a discussion of ITS with an example of its benefits in learning.It also overviews affect detection and responding in affectsensitive ITSs. Before concluding, the paper highlights some limitations of the AI learning systems to detectaffective states and achieve maximum student learning outcomes.