Earlier this year, researchers and experts shared the latest advances in AI technologies for students and teachers, offered insights on the future of teaching strategies and student assessment, and surfaced ethical and safety issues. Here are some takeaways from the event hosted in collaboration with Stanford Institute for Human-Centered Artificial Intelligence (HAI). To read the full story and watch the event recordings, visit: https://lnkd.in/g3sHqHD3
🔹 Amanda Bickerstaff, co-founder and CEO of AI for Education and a former high school teacher, said: “Teachers should be expert at teaching, and they should be augmented by technology to help them teach better.”
🔸 Candace Thille, associate professor at Stanford University Graduate School of Education (GSE) and faculty director of the Adult and Workforce Learning initiative of the Accelerator, identified several paths for AI assistance: grading, lesson planning, creating new and interesting questions and problems.
🔹 Victor Lee, associate professor at Stanford GSE and faculty lead for AI + Education at the Accelerator, shared a toolkit for teachers called CRAFT, which offers AI literacy resources for high school teachers in any subject.
🔸 Pat Yongpradit, the chief academic officer of Code.org, says his organization has developed AI guidance toolkits that cover AI in instruction and in policy.
🔹 Keith Krueger, CEO of the Consortium for School Networking (CoSN), said his association developed a “readiness” assessment for school districts to determine how prepared they are to roll out AI, covering operations, data, security, legal risk, and more.
🔸 Dorottya (Dora) Demszky, assistant professor of education at Stanford GSE, discussed how she involves teachers in the process of developing all her tools to ensure that new models are accurate and effective for marginalized learners.
🔹 Ge Wang, associate professor of music in the Stanford School of Humanities and Sciences, said we should critically evaluate our desires in the first place and the means to achieve them. “What are we doing with AI, what should we be doing with AI?” he asked the audience.
🔸 Emma Brunskill, associate professor of computer science in the Stanford University School of Engineering, explored how reinforcement learning improves AI tutors and assistants. One project, a learning game called DreamGrader, offers dense feedback on what parts of the game students struggled with. Brunskill said DreamGrader reduced grading time by 44% and improved accuracy by 6%.
🔹 Judith Fan, assistant professor of psychology in the Stanford School of Humanities and Sciences, offered a note of caution. Her lab, working to improve STEM education through AI, explored learning data visualization skills to find that humans still greatly outperform models: “I’m really excited for the next generation of AI teaching assistants and tutors, and I think they can have an enormous transformative impact on education."
Photos: Trevor Tachis