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Using Eye Tracking to Measure Implicit Learning in Students with LD, ADHD, and ASD (2017)

Description

Many students with LD, ADHD, and ASD tend to struggle in STEM classrooms. Often their struggles are rooted in Executive Function (EF) and language processing difficulties. Advances in data mining techniques that allow for nonintrusive measures of implicit learning are being explored by this project to develop a prototype adaptive version of a science learning game that can help diverse learners improve their understanding of core science concepts.

Our collaborative research team including researchers at TERC and MIT is collecting click stream and eye movement data for students playing an existing particle simulator game that has been shown to be predictive of learning outcomes. Previous work done by the EdGE team at TERC shows that students who show sound particle differentiation in their gameplay patterns tend to perform better on standard Newtonian physics items. Students who do not exhibit this is implicit knowledge in their gameplay pattern correspondingly don’t exhibit similar performance gains. By analyzing the game log and the eye movement patterns synchronized down to the millisecond level we are able to look for differences in attention allocation that are indicative of different student learning trajectories. This in turn will be used to create an adaptive prototype of the game able to strategically guide student attention in order to maximize learning.

NSF Award: 1417456

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Ibrahim Dahlstrom-Hakki

November 13, 2023 3:42 pm

Thank you for your interest in RtI project. While the work of this project has concluded, we have several other projects that have continued many of the lines of inquiry that began with this collaborative effort. Please feel free to post any questions regarding this work or any of our newer efforts building off of this initiative.

Traci Higgins

November 15, 2023 12:54 pm

Such an interesting project! This seems like an especially useful methodological approach for gaining understanding of how students with ADHD interact with and take in visual information because of the functional vision challenges and differences occurring at a high rate in this population. I am wondering whether there were findings that were specific to ADHD learners within this research. I am also really curious about elements of this work that may be more broadly informing your current work.

Ibrahim Dahlstrom-Hakki

November 16, 2023 12:52 pm

Reply to  Traci Higgins

We unfortunately were unable to disaggregate by profile because we didn’t have enough statistical power in each group. However, we definitely saw very different play profiles with some including very fast moving eye movements that were associated with less understanding of the underlying physics of the game and more of a “gamer” approach to solving the puzzles. We would like to take this work in the direction of using multi-sensory data to detect cognitive effort but unfortunately haven’t found the right solicitation for that idea yet.