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First Advisor

Jeremy Manning

First Advisor Department

Department of Psychological and Brain Sciences

Description

In our research, we wanted to explore whether we could track how people learn concepts in real-time by combining brain recordings with computational models of conceptual content. Our core question was: can we measure moment-by-moment learning as it happens in someone's brain?

To investigate this, we had 42 participants watch Khan Academy lectures on Earth Formation and Plate Tectonics while we recorded their brain activity using 64-channel EEG. We then created 90 quiz questions across three categories--Earth Formation, Plate Tectonics, and General Geology--to test what they actually learned from the videos. We used topic modeling, a computational technique, to extract and track the conceptual content from the video transcripts, allowing us to see how different concepts evolved throughout the lectures. We also calculated Inter-Subject Functional Correlation (ISFC), which essentially measures how synchronized participants' brain responses were during different parts of the videos. By aligning these brain synchronization patterns with our conceptual trajectories, we could explore whether brain activity patterns could predict learning outcomes.

Our findings were promising. We discovered that brain activity patterns, particularly in the gamma frequency band, differed significantly between questions that participants answered correctly versus incorrectly. This approach successfully linked specific moments in the lectures to learning outcomes, demonstrating that EEG signals can indeed help us track knowledge acquisition as it unfolds. Moving forward, we aim to leverage these brain-based learning signals to develop personalized, adaptive educational tools that could adjust teaching in real-time based on a student's ongoing brain activity.

Publication Date

Spring 5-26-2025

Keywords

learning, neuroeducation, EEG

Disciplines

Cognitive Science

Translating Neurophysiological Recordings into Dynamic Estimates of Conceptual Knowledge and Learning

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