AI
Literacy
for All
1st International Workshop on AI Literacy Education For All
26th International Conference on Artificial Intelligence in Education (AIED 2025)
Palermo, Italy
Half-Day Workshop at July 22, 2025, 14:00-16:00
As AI increasingly shapes society, ensuring that individuals across diverse backgrounds understand its capabilities, ethical implications, and societal impact is critical.
However, non-technical audiences—including K- 12 students, teachers, and workforce professionals—often lack the foundational AI literacy needed to navigate this evolving landscape responsibly. AI concepts, often cloaked in complex jargon and grounded in advanced mathematics, can be intimidating to newcomers, leading to limited enrollment in training programs or superficial engagement with existing resources.
This workshop will bring together educators, researchers, industry professionals, and policymakers to explore innovative approaches to AI literacy education. Attendees will collaboratively address challenges and opportunities in making AI education more accessible and effective.
Workshop
Goals
- Designing and evaluating AI literacy programs for K12 learners, teacher or workforce.
- Exploring educational technologies supporting AI literacy.
- Assessing AI literacy effectively and equitably.
- Developing pedagogies tailored for non- technical learners.
- Promoting diversity, equity, and inclusion in AI literacy initiatives.
Key
Dates
- Submission deadline:
May 19Extended to: May 31, 2025 - Notification of acceptance:
June 2Extended to: June 16, 2025 - Camera ready:
June 16Extended to: June 30, 2025 - Workshop Date: July 22, 2025
Topics
of Interest
We invite contributions covering:
- AI literacy frameworks and theoretical models
- Curriculum development for K-12, higher education, and workforce
- Teacher training models for AI education
- Workforce AI education and upskilling initiatives
- Novel assessment methods for AI literacy
Submission
Guidelines
We accept the following submission types:
- Full paper: 6-12 pages (including references)
- Poster: max 3 pages (including references), to showcase work in progress, preliminary results, or innovative AI Literacy learning materials
- Submission Format: Both submission types must adhere to the workshop's formatting guidelines and should be submitted using either LaTeX template or the DOCX template. Workshop proceedings will be published online via CEUR.
- Anonymity: The review process will be double-masked, meaning that both the authors and reviewers will remain anonymous.
- Submit your paper
Agenda
Registration
Keynote Speaker
Paper Presentation
Poster Presentation
Panel Discussion
Organizing
Committee
Please reach out to ruiweix@andrew.cmu.edu
if you have any questions.
Ruiwei Xiao
Carnegie Mellon University
Ruiwei Xiao is a PhD student in the Human-Computer Interaction Institute at Carnegie Mellon University and the co-founder of Active AI. Her research focuses on AI in education and AI literacy, with recent projects centered on helping computer science beginners interact with AI in a learning-oriented way, as well as creating scalable AI literacy modules for K-12 students and educators.
Ying-Jui Tseng
Carnegie Mellon University
Ying-Jui Tseng is a CMU alumni and a co-founder of Active AI. With years of UX design and AI-based learning design experiences for companies such as Amazon, IBM and PaGamO, he found Active AI and has provided AI Literacy solutions have benefits thousands of learners in Taiwan.
Hanqi Li
University of California, San Diego
Hanqi Li is an incoming PhD student at Department of Education, UCSD. She will be advised by Dr. Amy Eguchi, who takes part in the AI for K-12 initiative, jointly sponsored by AAAI and CSTA, as an advisory group member, working collaboratively with K-12 classroom teachers teaching CS who also took part in the development of the 2017 CSTA standards.
Guanze Liao
National Tsinghua University
Professor GuanZe Liao holds a Ph.D. in Design and currently serves as a Professor at the Institute of Learning Sciences and Technologies, National Tsing Hua University, Taiwan. His research expertise encompasses educational big data, digital textbook development policy, and implementing competency-oriented curriculum through learner-centered digital autonomous learning platforms. His current focus is on AI chatbot design and metaverse user experience, integrating artificial intelligence, educational technology, and design thinking to advance educational innovation.
John Stamper
Carnegie Mellon University
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. His work involves leveraging educational data mining techniques and the creation of data tools.
Ken Koedinger
Carnegie Mellon University
Dr. Ken Koedinger is a Professor of Human-Computer Interaction and Psychology at Carnegie Mellon University. His research has contributed to an understanding of student thinking and learning that has implications for educational technology and teaching. He has created cognitive models that have been used to create educational materials and technologies, including intelligent tutoring systems that adapt to student needs. His work combines cognitive science, artificial intelligence, and educational practice.
Program
Committee
Xu Wang
University of Michigan
Xu Wang is an Assistant Professor in Computer Science and Engineering and the School of Information (By courtesy) at the University of Michigan. Xu develops and advances human-AI collaborative techniques to support education. One of her research goals is to empower instructors and educators to create effective learning experiences more easily, which in turn supports scalable teaching and learning.
Jodi Davenport
WestEd
Jodi Davenport is Vice President of Learning, Technology, and Innovation at WestEd and Deputy Director of the Regional Educational Laboratory Northwest. She leads large-scale research initiatives that integrate cognitive science with education to improve student outcomes. Her work spans educational technology, learning science, and curriculum design, and has been cited over 1,500 times.
Amy Eguchi
University of California, San Diego
Dr. Amy Eguchi is a Teaching Professor at UC San Diego. Her research focuses on broadening participation in STEM+C through educational robotics, AI literacy, and K–12 computer science education. She promotes inclusive, hands-on learning using technologies like digital fabrication and robotics, with a focus on underrepresented groups. Amy also serves as an advisory group member for the AI for K–12 initiative, jointly sponsored by AAAI and CSTA.
Jionghao Lin
University of Hong Kong
Jionghao Lin is currently an Assistant Professor in Learning Technologies at the Faculty of Education, University of Hong Kong. His research interests include learning analytics, artificial intelligence in education, educational data mining, educational feedback, dialogue-based intelligent tutoring systems, and natural language processing. He focuses on the development of computational methods that can be used to understand and optimize the learning and teaching environment.
Jaromír Šavelka
Carnegie Mellon University
Jaromír Šavelka is a Research Associate in the School of Computer Science at Carnegie Mellon University and a member of the Technology for Effective and Efficient Learning (TEEL) Lab. His recent work explores the use of large language models (LLMs) in educational contexts, with a focus on computing education and AI literacy for both K–12 learners and the workforce.