Emotion Recognition in Self-Regulated Learning: Advancing Metacognition Through AI-Assisted Reflections

Metacognition, understood as the awareness of one’s own learning processes, plays a pivotal role in achieving effective learning outcomes. Recent work has shown the potential of AI-based emotion recognition technology to enhance learners’ metacognitive abilities during post-learning reflections. In this article, we present a novel interaction design that seamlessly integrates emotion recognition technology into the reflection process. The proposed solution captures and visualizes learners’ emotional states during self-regulated video-based learning activities, thereby facilitating deeper metacognition by offering insights into learners’ own emotions and those of their peers. We discuss the theoretical foundations of the proposed approach, its benefits, and ethical considerations for future research.