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Identifying Functions and Behaviours of Social Robots for In-Class Learning Activities: Teachers’ Perspective

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Abstract

With advances in artificial intelligence, research is increasingly exploring the potential functions that social robots can play in education. As teachers are a critical stakeholder in the use and application of educational technologies, we conducted a study to understand teachers’ perspectives on how a social robot could support a variety of learning activities in the classroom. Through interviews, robot puppeteering, and group brainstorming sessions with five elementary and middle school teachers from a local school in Canada, we take a socio-technical perspective to conceptualize possible robot functions and behaviours, and the effects they may have on the current way learning activities are designed, planned, and executed. Overall, the teachers responded positively to the idea of introducing a social robot as a technological tool for learning activities, envisioning differences in usage for teacher-robot and student-robot interactions. Further, Engeström’s Activity System Model—a framework for analyzing human needs, tasks, and outcomes—illustrated a number of tensions associated with learning activities in the classroom. We discuss the fine-grained robot functions and behaviours conceived by teachers, and how they address the current tensions—providing suggestions for improving the design of social robots for learning activities.

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Notes

  1. In the pedagogical literature, this system of classifying learners is controversial. Here, we report teachers’ perspectives as is without a critical analysis of their validity.

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Funding

This work was made possible by funding from

NSERC Discovery Grant RGPIN-2015-0454.

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Correspondence to Jessy Ceha.

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The study obtained ethics clearance from the University of Waterloo Research Ethics Committee (ORE #40392).

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Ceha, J., Law, E., Kulić, D. et al. Identifying Functions and Behaviours of Social Robots for In-Class Learning Activities: Teachers’ Perspective. Int J of Soc Robotics 14, 747–761 (2022). https://doi.org/10.1007/s12369-021-00820-7

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