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The team, led by University of Toronto Assistant Professor , has won the US$500,00 grand prize in the , a global competition to modernize, accelerate and improve the identification of effective learning tools and processes.

The team, which includes graduate students , , and 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 ��˾��ֱ��’s and a faculty affiliate at the . “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 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.”