Organizers

Ruiwei Xiao is a PhD student at Carnegie Mellon University (CMU) and co-founder of Active AI. Her research and startup experience are focused on AI Literacy Education. She organized the largest workshop at AIED 2025 (the previous edition of this proposed workshop). The AI literacy materials she developed have reached over 10k active users and 100k total users worldwide.

Shan Zhang is a PhD candidate in Educational Technology at the College of Education, University of Florida. Her research centers on multimodal AI literacy assessment and the design of theory-driven AI-powered learning technologies that foster AI literacy, enhance student engagement, and support meaningful interactions for sustained learning gains. Her recent work examines AI integration in K–12 education, collaborative learning and affect in STEM+C+AI contexts, and learner modeling.

Xinying Hou is a PhD candidate at the School of Information, University of Michigan, and a UMSI Dean’s Fellow. Her research focuses on two key facets of AI and education: educational actors with AI and AI for education, mainly focused on Computing education and AI literacy education. Her AI-powered computing learning tool has been integrated into Runestone Academy, a widely used online computing platform serving over 80,000 students annually. The AI literacy activities she created have also gained significant global reach.

Ying-Jui Tseng is a Carnegie Mellon University alumnus and Co-Founder of ActiveAI, a learning platform dedicated to advancing equitable AI literacy in K–12 education. With a background spanning UX design, AI, and learning sciences at organizations including Amazon, Junyi Academy, and PaGamO, he bridges research and practice to design impactful learning experiences. Through ActiveAI, he has led the development and large-scale implementation of AI literacy programs that have empowered over 20k learners and more than 200 educators, translating research into measurable classroom impact.

Qianou Ma is a PhD student at the Human-Computer Interaction Institute, Carnegie Mellon University. Her research focuses on training AI literacy, especially for non-experts in programming. She designs, builds, and evaluates LLM applications to help humans adapt and thrive in AI-infused development environments and optimize human‑AI collaboration.

Yash Tadimalla is a Computing Research Association (CRA) AI Education Fellows supporting research and outreach across multiple NSF-funded initiatives and serves as the lead Fellow for the NAIRR Pilot Expansion AI EDU RCN. As a passionate advocate for global STEM equity, Yash holds leadership roles with the United Nations Major Group for Children and Youth and the International Federation of Engineering Education Societies.

Bo Jiang is currently a professor at the Shanghai Institute of Artificial Intelligence for Education, East China Normal University, Shanghai, China. His research interests focus on educational large models, learner modeling, and K-12 AI education. He led the development of the first Chinese K–12 AI Curriculum Guideline and authored a seven-volume AI textbook series adopted by over 100 schools nationwide. He serves on the Executive Committee of APSCE and the editorial boards of journals including IEEE TLT, RPTEL, and IJBIC, and has chaired major conferences such as ICCE and GCCCE. He received the APSCE Early Career Research Award in 2021.

John Stamper is an Associate Professor at the Human-Computer Interaction Institute at Carnegie Mellon University and the Technical Director of the Pittsburgh Science of Learning Center DataShop. He is also the Director of the Masters of Educational Technology and Applied Learning Sciences (METALS) degree program.

Ken Koedinger is a the Hillman University Professor of Computer Science with appointments in Human Computer Interaction and Psychology at Carnegie Mellon University. Dr. Koedinger has an M.S. in Computer Science, a Ph.D. in Cognitive Psychology, and experience teaching in an urban high school. His multidisciplinary background supports his research goals of understanding human learning and creating educational technologies that increase student achievement. His research has contributed new principles and techniques for the design of educational software and has produced basic cognitive science research results on the nature of student thinking and learning. Koedinger directs LearnLab, which started with 10 years of National Science Foundation funding and is now the scientific arm of CMU’s Simon Initiative. LearnLab builds on the past success of Cognitive Tutors, an approach to online personalized tutoring that is in use in thousands of schools and has been repeatedly demonstrated to increase student achievement, for example, doubling what algebra students learn in a school year. He was a co-founder of CarnegieLearning, Inc. that has brought Cognitive Tutor based courses to millions of students since it was formed in 1998, and leads LearnLab, now the scientific arm of CMU’s Simon Initiative. Dr. Koedinger has authored over 250 peer-reviewed publications and has been a project investigator on over 45 grants. In 2017, he received the Hillman Professorship of Computer Science and in 2018, he was recognized as a fellow of Cognitive Science.

Program Committee

• TBA