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Remote learning settings require students to self-regulate their behavioral, affective, and cognitive processes, including preventing mind wandering. Such engagement in task-unrelated thoughts has a negative impact on learning outcomes and can occur with or without students’ awareness of it. However, research on the meta-awareness of mind wandering in education remains limited, predominantly relying on self-report measures that capture discrete information at specific time points. Therefore, there is a need to investigate and measure temporal dynamics in the meta-awareness of mind wandering continuously over time. This study examined the temporal patterns of 15 mind-wandering and meta-awareness probes in a sample of university students (N = 87) while they watched a video lecture. We found that the majority (60%) of mind wandering occurred with meta-awareness. Cluster analysis identified five distinct thought sequence clusters. Thought patterns dominated by unaware mind wandering were negatively associated with fact- and inference-based learning, whereas persistent aware mind-wandering patterns were linked to reduced deep-level understanding. Initial exploration into predictive modeling, based on eye gaze features, revealed that the models could distinguish between aware and unaware mind-wandering instances above the chance level (macro F1 = 0.387). Model explainability methods were employed to investigate the intricate relationship between gaze and mind wandering. It revealed the importance of eye vergence and saccade velocity in distinguishing mind-wandering types. The findings contribute to understanding mind-wandering meta-awareness dynamics and highlight the capacity of continuous assessment methods to capture and address mind wandering in remote learning environments. (PsycInfo Database Record (c) 2024 APA, all rights reserved)
