Optimizing Robot Tutors in Arithmetic Education

The goal of this project is to discover how robot teachers can be optimized to better respond to children's diverse learning needs. By examining robot behavioral styles and individual student differences, the project aims to develop long-term, effective interventions that improve learning outcomes and engagement in math education. 

This research uses neuroimaging and behavioral analysis to better understand how children respond to different robotic interventions. The findings may contribute to innovative, personalized solutions to current challenges in education, such as teacher shortages and lagging learning outcomes. 

• Improved understanding of how robot teachers can respond to individual learning needs. 
• Development of effective, personalized math interventions by a social robot. 
• Understanding the long-term effects of robots in math education. 

01 September 2024 - 01 September 2029

The project will be implemented through experiments with social robots in elementary schools, using neuroimaging and behavioral analysis. Research on different robot behavior styles and their influence on children's learning performance is at the core of the approach. 

This project has important significance for education and professional practice using social robots as innovative solutions to teacher shortages and the diverse needs of students. It promotes personalized learning, better supports children with math problems and attention disorders. In addition, the implementation of social robots can reduce teachers' workloads, contributing to a more sustainable educational environment. The results can lead to more inclusive teaching strategies, ensuring that all children, including those currently underrepresented, receive the attention and support they need.