Luke Eglington is a research scientist in DILab and contributes to the VERA, Jill Watson, and SAMI projects. His research focuses on developing and optimizing adaptive instructional systems (AIS) by accounting for principles of human learning and attention. For example, Luke recently published a paper showing how to create an AIS for maximally efficient spaced practice. Other research interests include individual student differences, mathematical models of learning, metacognition, and visual attention.
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