Boundary Conditions for AU-Based Detection of Understanding: A Literary Analysis Study

Large Language Models are increasingly being used by students in academic contexts, but they can only evaluate and engage with what students express in language. The feeling of understanding is inaccessible to them directly. This matters because the feeling of understanding shapes how students judge their understanding and guides their learning. Feelings have a physiological basis and can therefore be measured through facial action units. This study explored whether action unit patterns are associated with nascent understanding, misunderstanding, confusion, emergent understanding, deep understanding, and underconfidence as 198 participants completed a literary analysis task while their facial expressions were recorded over Zoom. CatBoost and logistic regression models demonstrated limited ability to discriminate phases at the population level, and within-person differences between phases were modest and inconsistent across participants. The findings highlight the difficulty of measuring the feeling of understanding in naturalistic academic contexts and may suggest that the feasibility of AU-based phase detection depends in part on the extent to which phases can be specified with temporal and conceptual precision.