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Professor John MITCHELL

Professor John MITCHELL

Mary And Gordon Crary Family Professor in the School of Engineering, and Professor, by Courtesy, of Electrical Engineering and of Education, Stanford University, USA

Biography

 

John C. Mitchell is the Mary and Gordon Crary Family Professor, Professor of Computer Science, and by courtesy Professor of Electrical Engineering and Professor of Education at Stanford University. He was previously Stanford Vice Provost for Teaching and Learning and Chair of the Computer Science Department. Mitchell’s research focuses on programming languages, computer security and privacy, blockchain, machine learning, and technology for education. Mitchell’s first research project in online learning started in 2009, when he and six undergraduate students built Stanford CourseWare, an innovative platform that expanded to support interactive video and discussion. CourseWare served as the foundation for initial flipped classroom experiments at Stanford and helped inspire the first massive open online courses (MOOCs) from Stanford. As Co-Director of the Lytics Lab, Carta Lab, and Pathways Lab, he has worked to improve educational outcomes through data-driven research and iterative design. His current education-related research projects are focused on collaborative learning and the use of generative AI. He currently serves as Faculty Director of the Hasso Plattner Institute of Design, which is also known as the Stanford d.school.

Title

Exploring GenAI for personal and collaborative learning

 

Abstract

The emergence of ChatGPT and other generative AI tools has created remarkable optimism about the power of AI for learning. For example, could AI provide personalized tutoring for students? Or easily customize teaching material for teachers? In addition to optimism, there is also concern about student cheating, and the potential need to revise the way we assess student progress. Many are also wondering how advances in AI will change what students need and want to learn. Summarizing a set of related research projects over the past year, this talk with look at promising directions and current questions about the use of generative AI. In addition to direct applications for students and teachers, we will also consider ways that generative AI can support collaborative learning. In a fall design course on collaborative learning with generative AI, several student teams produced prototype designs. Their curiosity and their reservations about the technology are provocative indicators of the future ahead.

 

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