Pupil dilation is known to indicate cognitive load. In this study, we looked at the average pupillary responses of a cohort of 29 undergraduate students during graphical problem solving. Three questions were asked, based on the same graphical input. The questions were interdependent and comprised multiple steps. We propose a novel way of analyzing pupillometry data for such tasks on the basis of eye fixations, a commonly used eyetracking parameter. We found that pupil diameter increased during the solution process. However, pupil diameter did not always reflect the expected cognitive load. This result was studied within a cognitive-load theory model. Higher-performing students showed evidence of germane load and schema creation, indicating use of the interdependent nature of the tasks to inform their problem-solving process. However, lower-performing students did not recognize the interdependent nature of the tasks and solved each problem independently, which was expressed in a markedly different pupillary response pattern. We discuss the import of our findings for instructional design.
Keywords: Cognitive-load theory; Eye tracking; Graph reading; Task-evolved pupillometry.