This paper explores the potential use of a social robot as tutor and playing partner in a primary school mathematics classroom. Our approach is using a math card game, based on the understanding of fractions, to study the pupil-robot interaction. We follow an iterative process consisting of three consecutive phases: (1) data collection involving a human playing partner, (2) a remotely controlled social robot as tutor and playing partner, and (3) a fully autonomous robotic tutor and playing partner. We present data collected from the phase 1 and 2 trials involving a total of 13 pupils (ages 10–12). The lessons learned from the first two phases are presented, as well as how these lessons can help inform future steps towards meeting the challenges presented by an autonomous robotic playing partner (phase 3).
In this paper we presented the Software Testing, AI and Robotics (STAIR) Learning Lab. STAIR is an initiative started at the University of Innsbruck to bring robotics, Artificial Intelligence (AI) and software testing into schools. In the lab physical and virtual learning units are developed in parallel and in sync with each other. Its core learning approach is based the develop of both a physical and simulated robotics environment. In both environments AI scenarios (like traffic sign recognition) are deployed and tested. We present and focus on our newly designed MiniBot that are both built on hardware which was designed for educational and research purposes as well as the simulation environment. Additionally, we describe first learning design concepts and a showcase scenario (i.e., AI-based traffic sign recognition) with different exercises which can easily be extended.
This study reasons that the sounds robots produce consequentially bring up the noise level in the classroom that might not benefit learning, and the perception of such sounds can impact the acceptability of the robot. Therefore, the consequential sounds of six different educational robots were studied on affective sound quality, and perception related to specific quality attributes of the robot producing the sound. The treatment was organized in a form of a live listening test, and sound impressions were collected by using a survey with nine five-point bipolar Likert items. Additionally, pupils were asked to rank the robots based on their respective sounds and appearance separately. As a result, observable differences were noted. mBot was rated most positively, followed by Thymio, and the worst ratings were attributed to the Jimu robot, probably due to the interaction of its caterpillar treads with the wooden surface. On the other hand, Jimu had the best ranking on behalf of its appearance. Cumulatively, based solely on the sounds, most pupils think that robots are safe, somewhat precise, robust, and working properly. However, the sounds are perceived as somewhat bothering, unpleasant and unusual and could distract pupils while learning. The full paper of this study can be retrieved from the project’s website ( https://www.zesoi.fer.hr/_download/repository/full_Perceptual_Evaluation_of_Educational_Robots_Consequential_Sounds.pdf ).
Social robots are at the beginning of their promising careers in various fields where social interactions take place. Whether they will be used in the classroom in the future, in what role and for what tasks, is still an open question. While pilot studies often emphasize the great potential in education, the social robots commercially available today cannot yet meet the high expectations. However, given the rapid pace of development, it is worth exploring the characteristics and usefulness of social robots for different learning and teaching purposes. We conducted semi-structured interviews with preservice teachers in business education as potential users of robot-assisted education to evaluate for what classroom teaching tasks a social robot would be suitable. The interviews were analyzed drawing from a framework for teaching quality comprising classroom management, student support, and cognitive activation. It became clear that, when considering ethical concerns, prospective teachers see the robot primarily in a supporting and assisting role to increase both student motivation and the competence experience. The interviewed preservice teachers have the intention to use social robots in the future. However, they stress the importance of more reliable technology and a highly interactive and ready-to-use learning scenario.
This contribution is dedicated to the establishment of futures literacy with the help of computational thinking In combination with robotics-based storytelling activities, the question will be explored to what extent this concept can contribute to making futures thinkable and how concrete realizations in primary education could look. To this purpose, pre-service teachers will apply the didactic design of the Tell, Draw & Code method. In a first step, the framing of futures literacy will be discussed, and the connection to the concept of computational thinking and the importance of language in the context of futures literacy will be shown. Subsequently, the developed project ideas on futures literacy and computational thinking are presented, in which storytelling activities are outlined.
