Real-time Brain Sensing for Learning Assessment

By integrating real-time brain input with an intelligent tutoring system, it would be possible to capture a learner’s changing cognitive state and adapt the learning experience appropriately. Working toward this goal, this project aims to use machine learning to classify a user’s cognitive state during a learning activity, using brain data collected with functional near-infrared spectroscopy, an emerging noninvasive neuroimaging tool. We will develop novel assessment methods of what students have learned and when moments of learning occur and use this as input to an intelligent tutoring system.