Analysing engineering expertise of high school students using eye tracking and multimodal learning analytics

In this paper, we describe results of a multimodal learning analytics pilot study designed to understand the differences in eye tracking patterns found to exist between students with low and high performance in three engineering-related computer games, all of which require spatial ability, problem-solving skills, and a capacity to interpret visual imagery. In the first game, gears and chains had to be properly connected so that all gears depicted on the screen would spin simultaneously. In the second game, students needed to manipulate lines so as to ensure that no two intersected. In the final game, students were asked to position gears in specific screen locations in order to put in motion onscreen objects. The literature establishes that such abilities are related to math learning and math performance. In this regard, we believe that understanding these differences in student’s visual processing, problem-solving, and the attention they dedicate to spatial stimuli will be helpful in making positive interventions in STEM education for diverse populations.