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Social robots can enhance deeper learning through social processes by providing companionship during typically isolated learning activities. Yet, there is limited exploration into the use of authoring tools for teachers to create and customize social robot-assisted lessons. To address this need, we present PATHWiSE, an authoring tool that utilizes teacher-in-the-loop AI-assisted verbal and non-verbal robot interaction design to customize RAL lessons to the needs and strengths of individual students and classrooms. We demonstrate the operation, AI-assist functions, and practical applications of the PATHWiSE UI. Our work underscores the need for developing tools for computing novices utilizing AI and RAL technologies 

We aim to design robotic educational support systems that can promote socially and intellectually meaningful learning experiences for students while they complete school work outside of class. To pursue this goal, we conducted participatory design studies with 10 children (aged 10–12) to explore their design needs for robot assisted homework. We investigated children’s current ways of doing homework, the type of support they receive while doing homework, and co-designed the speech and expressiveness of a homework companion robot. Children and parents attending our design sessions explained that an emotionally expressive social robot as a homework aid can support students’ motivation and engagement, as well as their affective state. Children primarily perceived the robot as a dedicated assistant at home, capable of forming meaningful friendships, or a shared classroom learning resource. We present key design recommendations to support students’ homework experiences with a learning companion robot. 

Teachers use interpersonal classroom skills to support their students’ learning in the classroom, but homework is done in isolation without the affordances of classroom interactions. Here we investigate how a homework tool could empower teachers to utilize their interpersonal classroom skills and provide new ways to support students outside of the classroom. Through three phases of interviews and co-design, we co-designed software for teachers to create their own robot-assisted homework activities. We found that teachers' existing expertise initially led to wrong assumptions about the tool but after viewing an exemplifying stimulus they shifted their mental model of the tool and of homework in general. These findings can help understand (1) how pedagogical expertise may hinder utilization of new tools, and (2) how a catalyst may shift existing perceptions and facilitate the use of new paradigms to support student learning. 

Educational technologies can provide students with adaptive feedback and guidance, but these systems lack personal interactions that make social and cultural connections to the student's own classroom and prior experiences. Social or companion robots have a high capacity for these types of interactions, but typically require advanced levels of expertise to program. In this study, we examined teachers use of an authoring tool to enable them to leverage their classroom-based expertise to design robot-assisted homework assignments, and explore how seeing a robot enact their designs influences their work. We found that the tool enabled the teachers to create novel social interactions for homework activities that were similar to their classroom interaction patterns. These interaction designs evolved over time and were shaped by the teacher's emerging mental model of the social robot, their concept of the students' perspective of these interactions, and a shift towards informal classroom-like interaction paradigms, thus transforming their view of what they can achieve with homework. We discuss how these findings demonstrate how the context of the activity can influence initial mental models of social activities and suggest practical guidance on designing authoring tools to best facilitate the creation of computer or robot supported social activities, such as homework.