Bayesian Active Learning-Based Robot Tutor for Children's Word-Reading Skills

Effective tutoring requires personalization of the interaction to each student. Continuous and efficient assessment of the student’s skills are a prerequisite for such personalization. We developed a Bayesian activelearning algorithm that continuously and efficiently assesses a child’s word-reading skills and implemented it in a social robot. We then developed an integrated experimental paradigm in which a child plays a novel story-creation tablet game with the robot. The robot is portrayed as a younger peer who wishes to learn to read, framing the assessment of the child’s wordreading skills as well as empowering the child. We show that our algorithm results in an accurate representation of the child’s word-reading skills for a large age range, 4-8 year old children, and large initial reading skill range. We also show that employing childspecific assessment-based tutoring results in an age- and initial reading skill-independent learning, compared to random tutoring. Finall...

• Type: Journal
• Year: 2015
• Where: AAAI
• Authors: Goren Gordon, Cynthia Breazeal
• Keywords: AAAI 2015, Intelligent Agents