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Multiuser Design of an Architecture for Social Robots in Education: Teachers, Students, and Researchers Perspectives

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Journal Front Robot AI
Date 2024 Dec 31
PMID 39737369
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Abstract

Research on social assistive robots in education faces many challenges that extend beyond technical issues. On one hand, hardware and software limitations, such as algorithm accuracy in real-world applications, render this approach difficult for daily use. On the other hand, there are human factors that need addressing as well, such as student motivations and expectations toward the robot, teachers' time management and lack of knowledge to deal with such technologies, and effective communication between experimenters and stakeholders. In this paper, we present a complete evaluation of the design process for a robotic architecture targeting teachers, students, and researchers. The contribution of this work is three-fold: (i) we first present a high-level assessment of the studies conducted with students and teachers that allowed us to build the final version of the architecture's module and its graphical interface; (ii) we present the R-CASTLE architecture from a technical perspective and its implications for developers and researchers; and, finally, (iii) we validated the R-CASTLE architecture with an in-depth qualitative analysis with five new teachers. Findings suggest that teachers can intuitively import their daily activities into our architecture at first glance, even without prior contact with any social robot.

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