Using Eye-tracking to Study Intuitive Reasoning on a Kinematics Graph Tasks

Understanding the ways that unconscious information processing occurs can help educators teach in more efficient ways.In any given science task, there are typically a myriad of relevant and irrelevant features that frame and direct reasoning pathways.To better train students to navigate task features productively, more needs to be understood about the ways that attention-attracting task features interact with reasoning processes.Eyetracking methodologies allow physics education researchers to record where a student allocates their attention, including the initial focus of attention.In this paper, we discuss results from eye-tracking research into a mechanic graph task that has a strong intuitive reasoning pathway that leads to an incorrect conclusion.We analyze data from students in algebra-based physics courses.We find that analysis of the eye-tracking metrics of first look and dwell time are consistent with predictions made from dual-process theories of reasoning.