Leveraging Eye-Tracking Technology to Understand How Young Children Solve a Mental Rotation Task

Relying on self-report to understand how children solve cognitive tasks has limitations, particularly with young children. Recent advances in eye-tracking technology allow researchers to leverage this tool to measure young children's strategies for solving cognitive tasks. The current study focuses on young children's mental rotation ability given its reported links to academic achievement in science, mathematics, and language arts. We explore the cognitive strategies employed by 3- to 7-year-olds using eye-tracking when they are solving mental rotation tasks. Prior literature shows participants use two types of cognitive strategies: holistic and piecemeal. Holistic involves the rotation of an object as a single entity, and piecemeal entails the rotation of an object by its individual components. Our final sample consisted of 148 three- to seven-year-old children (68 girls) from a local science museum. Participants completed a mental rotation task while having an eye-tracker record their eye movements. By using this data-driven approach, we identified how young children solve these tasks. Specifically, latent profile analysis using eye-tracking data revealed two distinct classes among the participants. Class 1, employing a holistic strategy, exhibited fewer visit and fixation counts and shorter visit durations. Class 2, employing a piecemeal strategy, demonstrated more visit and fixation counts along with greater visit durations. These findings show value in optimising eye-tracking technological advances to understand children's cognition and the efficacy of eye-tracking data in identifying how children approach and solve a mental rotation task.