Construction and Study of a Theoretical Model for Student Learning Evaluation Based on Facial Expression Recognition

Abstract

The rapid growth of online education has made accurate student learning evaluation challenging, as traditional methods often fail to capture real-time emotional states. Emotions play a key role in shaping motivation, cognition, and learning outcomes. Facial expressions, as observable indicators of emotions, offer a valuable approach for affect-aware learning evaluation. This paper proposes a theoretical model based on facial expression recognition, grounded in Control-Value Theory, Self-Determination Theory, and learning engagement theory. The model explains how emotions reflected in facial expressions infl uence motivation, cognition, and behavior, and establishes a framework linking facial expressions, emotional states, learning processes, and academic outcomes. This study lays the theoretical groundwork for future emotion-aware learning evaluation systems.