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STEM pattern

Cyber-learning to Detect and Combact Wandering Minds

Project Title: Attention-Aware Cyberlearning to Detect and Combat Wandering Minds

Research Team: Sidney D'Mello, James Brockemole, Matt Kloser

Funder & Grant Size: NSF $565,000

This project is developing an attention-aware version of Guru that detects and combats wandering minds. This will be done by studying mind wandering (MW) while high-school students supplement their biology classroom instruction via one-on-one learning sessions with Guru. We will leverage advances in consumer-grade eye tracking to develop an automated MW detector that monitors patterns of eye movements that are known to reveal the locus of visual attention. When MW is detected, Guru will dynamically intervene to restore attention to the learning task and attempt to correct learning deficits attributed to MW. Thus, the proposed exemplary implementation of an attention-aware Guru is intended to enrich the learning experiences of students by tackling the underexplored problem of MW during learning with technology. Our research questions include:

1.    What is the incidence of MW during learning with technology and how does MW vary with the level of interactivity afforded by the learning technology?
2.    How does MW correlate with learning outcomes?
3.    How is a subjective internal state like MW objectively manifested in eye movements and how can this information be leveraged to develop fully-automated gaze-based detectors of MW?
4.    Which intervention strategies are most effective at refocusing attention and compensating for the negative influence of MW on learning?
5.    What generalizable insights on MW, its manifestations in eye gaze, and interventions to combat it can we derive in order to inform the design of future attention-aware cyberlearning technologies?