Abstract: Pedagogical conversational agents (CA) support formal and informal learning to help students achieve better learning outcomes by providing information, guidance or fostering reflections. Even though the extant literature suggests that pedagogical CAs can improve learning outcomes, there exists no empirical evidence of what design features drive this effect. We will briefly report on a study we conducted in this field. Furthermore, we will provide a short demonstration of a quiz situation with a social robot (NAO), which will give insights how such a future learning context might look like. We envision a learning environment where pupils do not only interact with the social robot, but where the social robot is connected to other devices within the learning environment. For example, an external monitor to provide visual guidance, lights to darken or brighten the room, sounds to play certain tunes, etc. The study gave input to a research proposal to the European Commission, which will be presented as well. Amongst others, this project aims at better understanding how schoolchildren interact with pedagogical conversational agents and what new learning strategies emerge that are different to their traditional ones.

Bio: Isabella Seeber is an associate professor in the department of management, technology and strategy of Grenoble Ecole de Management. She conducts research at the intersection of collaborative engineering, crowdsourcing and innovation. Isabella's research focuses on AI-based conversational agents in team collaboration. She has published amongst others in Journal of Management Information Systems, Decision Support Systems, Computers in Human Behavior, Information & Management, or Group Decision and Negotiation.