TY - JOUR
AU - Mutlu, Bilge
AB -  Session: AI & Machine-Learning & Translation CHI 2012, May 5 “10, 2012, Austin, Texas, USA Pay Attention! Designing Adaptive Agents that Monitor and Improve User Engagement Dan Sza r, Bilge Mutlu Department of Computer Sciences, University of Wisconsin “Madison 1210 West Dayton Street, Madison, WI 53706, USA {dsza r,bilge}@cs.wisc.edu ABSTRACT tures Gestures Drops in attention Volume Embodied agents hold great promise as educational assistants, exercise coaches, and team members in collaborative work. These roles require agents to closely monitor the behavioral, emotional, and mental states of their users and provide appropriate, effective responses. Educational agents, for example, will have to monitor student attention and seek to improve it when student engagement decreases. In this paper, we draw on techniques from brain-computer interfaces (BCI) and knowledge from educational psychology to design adaptive agents that monitor student attention in real time using measurements from electroencephalography (EEG) and recapture diminishing attention levels using verbal and nonverbal cues. An experimental evaluation of our approach showed that an adaptive robotic agent employing behavioral techniques to regain attention during drops in engagement improved student recall abilities 43% over the baseline regardless of student gender and signi cantly improved female motivation and rapport. Our ndings 
TI - Pay attention!: designing adaptive agents that monitor and improve user engagement
DA - 2012-05-05
UR - https://www.deepdyve.com/lp/association-for-computing-machinery/pay-attention-designing-adaptive-agents-that-monitor-and-improve-user-CMNFa9ggJX
DP - DeepDyve
ER -