Evaluating students' understanding of statics concepts using eye gaze data

In engineering courses, exams and homework assignments are among the standard tools used to assess students' performance and comprehension of course material. However, they do not always provide opportunities to reveal whether students truly understand related engineering concepts. This paper seeks to bridge that research gap by using eye-tracking technology to observe how students solve statics problems. In a within-subject experiment, twenty participants were asked to solve nine statics problems shown on a computer display. A non-invasive eye-tracker was used to record participants' eye movements during the problem solving process. Participants were then asked to explain how they solved three representative problems. The results show that different eye gaze patterns exist between those who solved problems correctly and those who solved them incorrectly. For the specific concepts involved in solving these problems, those who correctly understood the concepts also exhibited different eye gaze patterns than those who did not. We also found that students' spatial visualization skills positively correlate with their performance when solving statics problems. This investigation showed that eye gaze data has the potential to serve as a diagnostic tool to discern how students solve statics problems and understand related engineering concepts. These results may provide insight into students' problem-solving strategies and difficulties, and help instructors choose more adaptive teaching methods for students.