Interactive Robotics in Education: Designing and Evaluating Adaptive Visual and Speech Interfaces

Abstract

This study explores the design and development of two adaptive interfaces—Visual and Speech Dialogue—for educational robots, guided by the CAM (Capability, Availability, Motivation) framework. Aiming to enhance parent-robot-child collaboration, the interfaces dynamically adjust to contextual factors such as user availability, subject familiarity, and emotional readiness. The Visual Interface provides a graphical platform for customizing daily study plans through user input, while the Speech Dialogue Interface leverages natural language processing and sentiment analysis to tailor robot responses during conversation. Each interface addresses unique situational needs: the Visual Interface supports structured learning with clear planning tools, while the Speech Interface enables hands-free, emotionally responsive interactions. Preliminary evaluation highlights the complementary strengths of both systems and their potential to support flexible, personalized educational experiences. By integrating user context into interaction design, this work advances the role of educational robotics in home learning environments. Future research will focus on real-world testing and iterative improvements to maximize usability, engagement, and pedagogical value.