Assistant Professor Joseph Jay Williams (front right) with graduate students on the Adaptive Experimentation Accelerator team, including (from left to right) Ilya Musabirov, Pan Chen, Harsh Kumar and Mohi Reza. (photo by Matt Hintsa)

U of T computer scientists’ team wins XPRIZE Digital Learning Challenge

The Adaptive Experimentation Accelerator team, led by University of Toronto Assistant Professor Joseph Jay Williams, has won the US$500,00 grand prize in the XPRIZE Digital Learning Challenge, a global competition to modernize, accelerate and improve the identification of effective learning tools and processes.

The team, which includes graduate students Ilya Musabirov, Mohi Reza, Pan Chen and Harsh Kumar from the department of computer science, as well as collaborators from Carnegie Mellon University and North Carolina State University, built a tool that uses AI-driven experiments to personalize students’ learning experiences.

“Students need help to learn and manage themselves, but every student is different, says Williams, who is a member of U of T’s Data Sciences Institute and a faculty affiliate at the Vector Institute for Artificial Intelligence. “Teachers also need support to know what to say and how to explain it to such a diverse range of students from different backgrounds, with different life experiences.”

The researchers’ dedication to improving learning outcomes for students is clear, says Eyal de Lara, professor and chair of the department of computer science, and their novel approach is a “significant contribution to the areas of human-computer interaction and educational technology.”

“I am thrilled to congratulate Professor Williams and his incredible group of students on their grand-prize-winning innovation, a tool that bridges machine learning and human psychology to customize curricula and maximize student success,” says Melanie Woodin, dean of the Faculty of Arts & Science. “I look forward to students benefitting from the Adaptive Experimentation Accelerator in future classrooms.”

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