Eye-Tracking in STEM Education Research: Limitations, Experiences and Possible Extensions

Abstract

Eye-tracking technology is being increasingly used in science, technology, engineering and mathematics (STEM) education research. However, most available eye-tracking devices are oriented towards research problems focusing on attention, particularly in areas such as advertising, linguistics, human factors, human-computer interaction, training simulators, sports and virtual reality. Problems in these areas are fundamentally different from those in STEM education, where attention is only one of the many important variables in teaching-learning. Since learning is a process happening over time, STEM investigations focus on understanding the learning process, and this requires moving beyond attention information, doing sophisticated analysis of fixation data, and ways of collecting richer data that support such process analysis. In this paper, we present our difficulties and experiences in using standard eye-tracking systems to understand the learning process. We also describe some new methods developed to collect and analyze process data, and propose several possible extensions to eye tracking systems that would make eye tracking more useful for STEM education research.