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Identifying critical conceptual moments during a lecture where neural encoding patterns distinguish successful from unsuccessful learners

Poster Session A - Saturday, March 7, 3:00 – 5:00 pm, Fairview/Kitsilano Ballrooms

Yeongji Lee¹ (yeongji.lee.gr@dartmouth.edu), David Kraemer; ¹Dartmouth College

Successful learning depends on capturing underlying relationships between concepts, not just understanding individual concepts or surface-level details. Our prior behavioral work demonstrated that the semantic structure of a lecture video predicts which information students remember. Critically, we identified specific information units in the lecture that bridge multiple concepts and capture fundamental relationships—units whose recall strongly predicts an individual's conceptual understanding. Successful learners remember this integrative information while struggling learners do not, suggesting that students could diverge onto different learning trajectories depending on whether they successfully encode these conceptual connections. In this fMRI study, participants (N = 63) watched the same 15-minute lecture covering Newtonian physics concepts, then verbally recalled what they learned and remembered while in the scanner. Using the critical information units identified in our prior behavioral study, we applied multivariate pattern analysis (MVPA) at the specific time windows when this critical information was presented. We trained SVM classifiers to distinguish neural patterns at each time point between the participants who subsequently showed high versus low conceptual understanding as rated by human raters. This work provides insight into a neural mechanism for how abstract conceptual knowledge emerges during naturalistic educational experiences, with implications for adaptive instructional design and real-time assessment of conceptual learning.

Topic Area: THINKING: Reasoning