The dual role of humanoid robots in education: As didactic tools and social actors

Abstract

The idea of using social robots for teaching and learning has become increasingly prevalent and robots are assigned various roles in different educational settings. However, there are still few authentic studies conducted over time. Our study explores teachers' perceptions of a learning activity in which a child plays a digital mathematics game together with a humanoid robot. The activity is based on the idea of learning-by-teaching where the robot is designed to act as a tutee while the child is assigned the role of a tutor. The question is how teachers perceive and talk about the robot in this collaborative child-robot learning activity? The study is based on data produced during a 2-years long co-design process involving teachers and students. Initially, the teachers reflected on the general concept of the learning activity, later in the process they participated in authentic game-play sessions in a classroom. All teachers' statements were transcribed and thematically coded, then categorized into two different perspectives on the robot: as a social actor or didactic tool. Activity theory was used as an analytical lens to analyze these different views. Findings show that the teachers discussed the activity’s purpose, relation to curriculum, child-robot collaboration, and social norms. The study shows that teachers had, and frequently switched between, both robot-perspectives during all topics, and their perception changed during the process. The dual perspectives contribute to the understanding of social robots for teaching and learning, and to future development of educational robot design.

Expecting, understanding, relating, and interacting-older, middle-aged and younger adults’ perspectives on breakdown situations in human–robot dialogues

“…Rozendaal et al (2019) ; Rozendaal et al (2020) and Ekström and Pareto (2022) have explored robotic agents (robotic ball, robotic backpack, Pepper as a social, and educational robot) playing interchangeable roles between a tool and an agent, which aligns with the design implications on the theme relating emphasized in this work. The results and design implications of this work suggest that a social robot should be able to transition between a tool and an agent, and between different roles an agent can play, such as a professional, a companion, and an assistant.…”

“…The design implications suggested in this work aim to expand this understanding, and 'understand' knowledge and intentions at different levels of activity in activity-theoretical terms, where motive and conflicts at a higher level of activity relate to intentions and underlying needs, and at the lower level of activity relate to knowledge about the facts, procedures, and social norms. Rozendaal et al (2019); Rozendaal et al (2020) and Ekström and Pareto (2022) have explored robotic agents (robotic ball, robotic backpack, Pepper as a social, and educational robot) playing interchangeable roles between a tool and an agent, which aligns with the design implications on the theme relating emphasized in this work. The results and design implications of this work suggest that a social robot should be able to transition between a tool and an agent, and between different roles an agent can play, such as a professional, a companion, and an assistant.…”

“…Their results suggested that the participating hospitalized children and their parents treated and played with the robot as a thing, a tool, or an agent, and that there was a shift between the roles. Ekström and Pareto (2022) use Activity Theory as an analytical lens to understand collaborative learning activity with a social educational robot in a classroom. The Engeström's activity system model (Engeström, 1999a) was used to understand the needs of the children, the tasks, and the outcomes.…”

“… Ekström and Pareto (2022) use Activity Theory as an analytical lens to understand collaborative learning activity with a social educational robot in a classroom. The Engeström’s activity system model ( Engeström, 1999a ) was used to understand the needs of the children, the tasks, and the outcomes.…”

An Exploration of the Pepper Robot’s Capabilities: Unveiling Its Potential

“…When Pepper hears a sound, it orients itself toward the person who created the sound (claps or voice), establishing and maintaining eye contact with that person. Carros et al [16] found that Pepper's speech recognition was not always accurate with elderly people, while Ekstrom et al [17] noted that it had difficulty interacting with children. However, children were found to be motivated and engaged in the presence of Pepper [18].…”