Learning and Teaching in Co-Adaptive Guidance for Mixed-Initiative Visual Analytics

Abstract

Guidance processes in visual analytics applications often lack adaptivity. In this position paper, we contribute the concept of co-adaptive guidance, building on the principles of initiation and adaptation. We argue that both the user and the system adapt their data-, task- and user/system-models over time. Based on these principles, we propose reasoning about the guidance design space through introducing the concepts of learning and teaching that complement the existing dimension of implicit and explicit guidance, thus, deriving the four guidance dynamics user-teaching, system-teaching, user-learning, and system-learning. Finally, we classify current guidance approaches according to the dynamics, demonstrating their applicability to co-adaptive guidance.