What Should the Agent Withhold? Designing Cognitive Friction Against Over-Reliance in Visualization Design Learning

Abstract

Students learning visualization design increasingly use GenAI-powered authoring tools, which can produce a chart from a short natural-language description. While these tools lower the barrier to producing visualizations, they also allow learners to produce a satisfactory chart without making the design decisions the exercise was intended to develop, which can give an illusion of competence while leaving design skills underdeveloped. In this position paper, we make a case for AI agents that facilitate cognitive friction as a strategy to support visualization design learning. We define friction for this setting, distinguish it from the incidental cost of a difficult interface, and organize it by the point in the learner–agent loop at which it intervenes, yielding three positions. We then describe five skills an agent needs to deliver friction at these positions. We illustrate both the positions and the skills through a chart-critique exercise suited to introductory visualization teaching. We then discuss what would be needed to test whether an agent with these skills actually supports learners’ design reasoning.