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ORIGINAL RESEARCH article

Front. Robot. AI
Sec. Human-Robot Interaction
Volume 11 - 2024 | doi: 10.3389/frobt.2024.1409671
This article is part of the Research Topic Advances in Robots for Learning View all 5 articles

Multiuser Designing of an Architecture for Social Robots in Education: Teachers, Students, and Researchers perspectives

Provisionally accepted
  • 1 Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland
  • 2 University of São Paulo, São Carlos, São Carlos, São Paulo, Brazil

The final, formatted version of the article will be published soon.

    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. For instance, students' motivations and expectations towards 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 are presenting a complete evaluation of the designing process for a robotic architecture targeting teachers, students, and researchers. The contribution of this work is threefold: (i) we first present a high-level assessment of the performed studies 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-study of qualitative analysis with 5 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.

    Keywords: Social Robots, Education, HRI, teachers, Children-robot interaction, Interactive design

    Received: 30 Mar 2024; Accepted: 30 Oct 2024.

    Copyright: © 2024 Tozadore and Romero. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Daniel Tozadore, Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.