Measuring Cognitive Load in Multiplication: An Eye-Tracking Study

• In Event: Roundtable Session 52
  In Roundtable Session: Cognition and Learning

Abstract

Multiplication is difficult for students, especially when involving multi-digit operands and carry-digit. In this study, eye and hand movement data have been simultaneously collected while five students were working on two-digit multiplication problems with traditional algorithm and Treviso algorithms. To understand the underpinning cognitive process of multiplication within and between the algorithms, we examined the trajectory of eye fixations, duration of fixations and the change of pupil size. Preliminary data analysis indicated that certain aspects of the traditional algorithm have placed a higher cognitive load on participants, as compared to other parts. The Treviso algorithm is found to be less cognitively demanding. Eye and hand movement data proves to be a reliable measure of change in cognitive load over time.

Authors

• Jiahui Wang, University of Florida

• Matthew H. Schneps, Smithsonian Astiophysical Observatory

• Pasha Antonenko, University of Florida

• Marc Pomplun, University of Massachusetts - Boston