Children's learning-by-teaching with a social robot versus a younger child: Comparing interactions and tutoring styles.

Human peer tutoring is known to be effective for learning, and social robots are currently being explored for robot-assisted peer tutoring. In peer tutoring, not only the tutee but also the tutor benefit from the activity. Exploiting the learning-by-teaching mechanism, robots as tutees can be a promising approach for tutor learning. This study compares robots and humans by examining children's learning-by-teaching with a social robot and younger children, respectively. The study comprised a small-scale field experiment in a Swedish primary school, following a within-subject design. Ten sixth-grade students (age 12-13) assigned as tutors conducted two 30 min peer tutoring sessions each, one with a robot tutee and one with a third-grade student (age 9-10) as the tutee. The tutoring task consisted of teaching the tutee to play a two-player educational game designed to promote conceptual understanding and mathematical thinking. The tutoring sessions were video recorded, and verbal actions were transcribed and extended with crucial game actions and user gestures, to explore differences in interaction patterns between the two conditions. An extension to the classical initiation-response-feedback framework for classroom interactions, the IRFCE tutoring framework, was modified and used as an analytic lens. Actors, tutoring actions, and teaching interactions were examined and coded as they unfolded in the respective child-robot and child-child interactions during the sessions. Significant differences between the robot tutee and child tutee conditions regarding action frequencies and characteristics were found, concerning tutee initiatives, tutee questions, tutor explanations, tutee involvement, and evaluation feedback. We have identified ample opportunities for the tutor to learn from teaching in both conditions, for different reasons. The child tutee condition provided opportunities to engage in explanations to the tutee, experience smooth collaboration, and gain motivation through social responsibility for the younger child. The robot tutee condition provided opportunities to answer challenging questions from the tutee, receive plenty of feedback, and communicate using mathematical language. Hence, both conditions provide good learning opportunities for a tutor, but in different ways.

Comparing a Robot Tutee to a Human Tutee in a Learning-By-Teaching Scenario with Children.

Social robots are increasingly being studied in educational roles, including as tutees in learning-by-teaching applications. To explore the benefits and drawbacks of using robots in this way, it is important to study how robot tutees compare to traditional learning-by-teaching situations. In this paper, we report the results of a within-subjects field experiment that compared a robot tutee to a human tutee in a Swedish primary school. Sixth-grade students participated in the study as tutors in a collaborative mathematics game where they were responsible for teaching a robot tutee as well as a third-grade student in two separate sessions. Their teacher was present to provide support and guidance for both sessions. Participants' perceptions of the interactions were then gathered through a set of quantitative instruments measuring their enjoyment and willingness to interact with the tutees again, communication and collaboration with the tutees, their understanding of the task, sense of autonomy as tutors, and perceived learning gains for tutor and tutee. The results showed that the two scenarios were comparable with respect to enjoyment and willingness to play again, as well as perceptions of learning gains. However, significant differences were found for communication and collaboration, which participants considered easier with a human tutee. They also felt significantly less autonomous in their roles as tutors with the robot tutee as measured by their stated need for their teacher's help. Participants further appeared to perceive the activity as somewhat clearer and working better when playing with the human tutee. These findings suggest that children can enjoy engaging in peer tutoring with a robot tutee. However, the interactive capabilities of robots will need to improve quite substantially before they can potentially engage in autonomous and unsupervised interactions with children.

Trouble and Repair in Child-Robot Interaction: A Study of Complex Interactions With a Robot Tutee in a Primary School Classroom.

Today, robots are studied and expected to be used in a range of social roles within classrooms. Yet, due to a number of limitations in social robots, robot interactions should be expected to occasionally suffer from troublesome situations and breakdowns. In this paper, we explore this issue by studying how children handle interaction trouble with a robot tutee in a classroom setting. The findings have implications not only for the design of robots, but also for evaluating their benefit in, and for, educational contexts. In this study, we conducted video analysis of children's group interactions with a robot tutee in a classroom setting, in order to explore the nature of these troubles in the wild. Within each group, children took turns acting as the primary interaction partner for the robot within the context of a mathematics game. Specifically, we examined what types of situations constitute trouble in these child-robot interactions, the strategies that individual children employ to cope with this trouble, as well as the strategies employed by other actors witnessing the trouble. By means of Interaction Analysis, we studied the video recordings of nine group interaction sessions (n = 33 children) in primary school grades 2 and 4. We found that sources of trouble related to the robot's social norm violations, which could be either active or passive. In terms of strategies, the children either persisted in their attempts at interacting with the robot by adapting their behavior in different ways, distanced themselves from the robot, or sought the help of present adults (i.e., a researcher in a teacher role, or an experimenter) or their peers (i.e., the child's classmates in each group). In terms of the witnessing actors, they addressed the trouble by providing guidance directed at the child interacting with the robot, or by intervening in the interaction. These findings reveal the unspoken rules by which children orient toward social robots, the complexities of child-robot interaction in the wild, and provide insights on children's perspectives and expectations of social robots in classroom contexts.

Virtual TeleRehab: a case study.

We examined the efficacy of a remotely based occupational therapy intervention. A 40-year-old woman who suffered a stroke participated in a telerehabilitation program. The intervention method is based on virtual reality gaming to enhance the training experience and to facilitate the relearning processes. The results indicate that Virtual TeleRehab is an effective method for motivational, economical, and practical reasons by combining game-based rehabilitation in the home with weekly distance meetings.