Schools are meant to prepare learners for the future outside of school. Current developments in AI, machine learning and robotics suggests a future of fully shared social spaces, including learning environments (LEs), with robotic personalities. Today’s learners (as well as teachers) should be prepared for such a future. AI in Education (AIED) has focused on implementation of online and screen-based Pedagogical Agents (PAs); however, research findings support richer learning experiences with embodied PAs, hence, recent studies in AIED have focused on robot as peers, teaching assistants or as instructional materials. Their classroom uses employ gamification approaches and are mostly based on a one-robot- one-student interaction style whereas current educational demands support collaborative approaches to learning.
Robots as instructors are novel, considered a major challenge due to the requirements for good teaching, including the demands for agency, affective capabilities and classroom control which machines are believed to be incapable of. Current technological capabilities suggest a future with full-fledged robot teachers teaching actual classroom subjects, hence, we implement a robot teacher with capabilities for agency, social interaction and classroom control within a collaborative learning scenario involving multiple human learners and the teaching of basic Chemistry in line with current focus on STEM areas. We consider the PI pedagogical approach an adequate technique for implementing robotic teaching based on its design with inherent support for instructional scaffolding, learner control, conceptual understanding and learning by teaching. We are exploring these features in addition to the agentic capabilities of the robot and the effects on learner agency as well as improved learning in terms of engagement, learner control and social learning. In the future, we will focus on other key concepts in learning (e.g. assessment), other types of learners (e.g. learners with cognitive/physical disabilities), interaction styles and LEs. We will also explore and cross-community approaches that leverage on integration of sibling communities.