Affective Robot Behavior Improves Learning in a Sorting Game - Robotics Institute Carnegie Mellon University
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PhD Speaking Qualifier

May

9
Mon
Roshni Kaushik PhD Student Robotics Institute,
Carnegie Mellon University
Monday, May 9
11:00 am to 12:00 pm
GHC 4405
Affective Robot Behavior Improves Learning in a Sorting Game

Abstract:
Nonverbal communication in the field of education can allow teachers to emotionally support their students and improve educational experience and performance. Robot nonverbal movements have been shown to improve both subjective experiences and task performance, and this work investigates whether affective robot behavior can improve human learning. This is tested using an online sorting game where players learn easy or difficult rules, aided by robot feedback videos that contain either neutral or affective movements. Results indicate that affective robot behavior improves learning of the sorting rules and reduces the perceived difficulty of the task.

Committee:
Reid Simmons
Henny Admoni
Jean Oh
Michael Lee