This lab is a group of professors in the Computer Science department with a common interest in advancing education using computer science techniques. We are part of a greater mission at Stanford university, and beyond, to make high quality, inclusive education more accessible to all. We work on a broad set of projects including: AI to understand human learners, new ways to get humans to learn from and teach each other, and better designs for learning experiences.
Post Doc job: We are actively hiring Post Docs to work on a joint project between the School of Education and the CS Department. See the full post doc ad. We welcome applicants from anywhere in the world.
Stanford PhD student: If you are a Stanford PhD student in the CS department, and you are interested in education please reach out to the professors.
HAI Hoffman-Yee Grant Winner, 2020. AI Tutors for Creative Open-Ended Domains: Readying Learners for the 21st century Workforce.
Best paper award, EDM 2020. Variational Item Response Theory: Fast, Accurate, and Expressive.
Outstanding student paper award, AAAI 2019. Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference.
Top ten papers of all time (#4), SIGCSE 2019. A Multi-institutional Study of Peer Instruction in Introductory Computing.
The Stanford Computer Science department has a long history of contributing to the field of education. Researchers in the department created the Coursera and Udacity MOOC platforms, have contribued core ideas to AI for education, including Deep Knowledge Tracing and Variational Item Response Theory, tools to facilitate collaborative human learning and more.
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