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bioRxiv · 10.1101/2025.05.02.651980

State and trait measures of attention predict performance in video-based learning

Abstract

Poor academic performance is often linked to attention deficits, but it remains unclear whether these reflect enduring traits or momentary lapses in focus. In this study, we examined how state and trait-level attention relate to learning from short educational videos. Across four experiments (N = 152), participants completed standardized assessments of inattention, hyperactivity, working memory capacity, and GPA. They then viewed 3-6-minute educational videos while electroencephalography (EEG) tracked neural responses, followed by quizzes assessing short-term retention. Neural synchrony during video viewing, a measure of attentional state, strongly predicted test performance (p < 0.001). In contrast, trait inattention did not predict retention (p > 0.05), although it was negatively associated with GPA. Attentional state was positively associated with working memory capacity but not with trait inattention. These findings suggest that students with attentional difficulties can still learn effectively from short, engaging content, emphasizing the importance of instructional format in supporting diverse learners.

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BibTeXRIS

Madsen, J., Parra, L. C.. 2025-05-05. State and trait measures of attention predict performance in video-based learning. https://doi.org/10.1101/2025.05.02.651980

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