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Duke Launches Center to Bring Computational Thinking to All Students


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Duke University West Campus Union

The CCT will provide customized training in computation, modeling, data science, and the ethics of emerging technologies.

Credit: Front Inc.

Duke University's newly launched Center for Computational Thinking (CCT) is intended to meet growing demands for more computational skills among new college graduates. It will infuse data literacy across the academic experience while simultaneously preparing students to consider the ethical, legal, and social impacts of technology.

"The CCT will provide training in a co-curricular seminar-style to complement traditional Duke classes, and inspire curricular innovation," says Tracy Futhey, Duke's vice president for information technology and chief information officer.

The CCT represents a core priority within Duke Science and Technology, a faculty hiring and fundraising effort designed to create sustained support for discovery science and strategic investments in specific areas of science and technology across all of Duke.

"The departments of Computer Science, Electrical and Computer Engineering, Mathematics, and Statistical Science will play a central role in CCT by innovating their pedagogy, introducing new pathways into the disciplines and further refining existing curriculum," says Trinity College of Arts & Sciences Dean Valerie Ashby. "But we also recognize that we want all Duke students to be computationally literate — regardless of major or minor. Computational thinking is about adopting a specific mindset and approach to problem solving. This is liberal arts for the 21st century."

For students in traditional computational majors, the CCT will introduce the latest computational tools, demonstrating how concepts learned in the classroom can translate to practical, real-world applications.

For students in non-computational majors, the CCT will align computational principles and methods with broader student interests, such as integrating image-analysis techniques into biology courses or using natural language processing for history, literature, or law.

From Duke University
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