Multiuser design of an architecture for social robots in education: teachers, students, and researchers perspectives

Front Robot AI. 2024 Dec 16:11:1409671. doi: 10.3389/frobt.2024.1409671. eCollection 2024.

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.

Keywords: HRI; children–robot interaction; education; interactive designn; social robots; teachers.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was partially funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001, the Fundação de Amparo á Pesquisa do Estado de São Paulo (FAPESP), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), and the EPFL internal grants: Proposal 24866/External grant: 10339. Open access funding by Swiss Federal Institute of Technology in Lausanne (EPFL).