Masayoshi Kanon
Papers
1
Total Citations
2
H-Index
1
About
Masayoshi Kanon’s research lies at the intersection of human-robot interaction, educational technology, and affective computing. His most cited work, “Psychological effects of educational-support robots using an emotional expression model” (2014), addresses a critical challenge in educational robotics: sustaining user engagement over time. Kanon proposed an emotional expression model for learning-assist robots, designed to make interactions feel more natural and responsive, thereby preventing the loss of interest that often plagues human-robot educational settings. Although his citation count is modest—with his top paper accruing 2 citations—his contribution is notable for its early focus on the psychological dimensions of robot-assisted learning, a field that has since grown substantially. Kanon’s work anticipates later developments in socially assistive robotics and affective human-agent interaction, making him a thoughtful pioneer in understanding how robots can emotionally support learners. His research continues to inform the design of more empathetic and engaging educational robots, highlighting the importance of emotional expression in sustaining meaningful human-robot relationships.
Research Focus
Key Achievements
Top Papers
- 1