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1. AI Learning Priorities for All K-12 Students

   Twarek, Bryan; Koressel, Jacob; Gardner-McCune, Christina; Touretzky, David (May 2025, Computer Science Teachers Association)

   Rapid changes in artificial intelligence (AI) require changes in how and what is taught about AI to K-12 students. These changes will ensure that students are prepared to be smart consumers and competent creators of AI, as well as informed citizens. To meet this need, CSTA, in partnership with AI4K12, spearheaded the Identifying AI Priorities for All K-12 Students project. The project gathered experts – including teachers, researchers, administrators, and curriculum developers – to articulate priorities for AI education. This report summarizes the result of that effort. The project had four goals: 1. Identify priorities for AI learning across each K-12 grade band. As a result of a collaborative, iterative process, the project articulated five categories for AI learning: Humans and AI, Representation and Reasoning, Machine Learning, Ethical AI System Design and Programming, and Societal Impacts of AI. 2. Suggest updates to the AI4K12 Guidelines. Advances in generative AI necessitate updates to the AI4K12 Guidelines. This is especially true for Big Idea #4: Natural Interaction, since generative AI represents a substantial advance in the ability of AI to interact with humans. Similarly, generative AI raises many ethical questions relevant to Big Idea #5: Societal Impacts. 3. Advance the research agenda for K-12 AI education. Priorities for research in AI education include the importance of supporting teachers, promoting inclusive and student-centered pedagogies, developing appropriate tools, gaining a better understanding of AI’s impact on learning, and ensuring equity in AI education. 4. Share promising practices across the AI and CS education communities. Participants shared their work in AI education. While the practices described varied, there were some common themes. Concerns about ethics and responsible AI were foregrounded, and hands-on learning activities were featured prominently. Meeting the needs of all children was a key concern, with approaches and tools that are widely accessible as well as engaging for all students. As a result of these common themes, we offer related recommendations for AI curriculum and instruction. The report also includes an exploration of the tensions and challenges that emerged from the project, such as the difficulty of categorizing, organizing, and prioritizing learning content. Preparing students to succeed personally and professionally in a world powered by computing will require rigorous, high-quality, and equitable learning opportunities in AI education. This project sought to determine priorities for AI education for all students to learn as part of a robust foundation in computer science, as well as options for more comprehensive study of AI. Within and across these priorities, two themes stand out. First, all students need to explore the personal, societal, and environmental impacts – both positive and negative – of AI. Second, students need to develop a broad conceptual understanding of how AI works: a frequent refrain from the project’s participants was that students need to understand that “AI isn’t magic.” While implementing high quality AI education, at scale, for all students will be challenging, the work already undertaken by convening participants demonstrates that there are elements of a foundation in place, one that can be built upon to ensure that all students are prepared to flourish in a world powered by computing. 

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2. A Year in K-12 AI Education

   https://doi.org/10.1609/aimag.v40i4.5289  

   Touretzky, David; Gardner-McCune, Christina; Breazeal, Cynthia; Martin, Fred; Seehorn, Deborah (January 2020, AI Magazine)

   The time is ripe to consider what 21st-century digital citizens should know about artificial intelligence (AI). Efforts are under way in the USA, China, and many other countries to promote AI education in kindergarten through high school (K–12). The past year has seen the release of new curricula and online resources for the K–12 audience, and new professional development opportunities for K–12 teachers to learn the basics of AI. This column surveys the current state of K–12 AI education and introduces the work of the AI4K12 Initiative, which is developing national guidelines for AI education in the USA.   A Note to the Reader This is the inaugural column on AI education. It aims to inform the AAAI community of current and future developments in AI education. We hope that the reader finds the columns to be informative and that they stimulate debate. It is our fond hope that this and subsequent columns inspire the reader to get involved in the broad field of AI education, by volunteering their expertise in their local school district, by providing level-headed input when discussing AI with family and friends or by lending their considerable expertise to various decision makers. We welcome your feedback, whether in the form of a response to an article or a suggestion for a future article. – Michael Wollowski, AI in Education Column Editor 

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3. Envisioning AI for K-12: What Should Every Child Know about AI?

   https://doi.org/10.1609/aaai.v33i01.33019795  

   Touretzky, David; Gardner-McCune, Christina; Martin, Fred; Seehorn, Deborah (July 2019, Proceedings of the AAAI Conference on Artificial Intelligence)

   The ubiquity of AI in society means the time is ripe to consider what educated 21st century digital citizens should know about this subject. In May 2018, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for teaching AI to K-12 students. Inspired by CSTA's national standards for K-12 computing education, the AI for K-12 guidelines will define what students in each grade band should know about artificial intelligence, machine learning, and robotics. The AI for K-12 working group is also creating an online resource directory where teachers can find AI- related videos, demos, software, and activity descriptions they can incorporate into their lesson plans. This blue sky talk invites the AI research community to reflect on the big ideas in AI that every K-12 student should know, and how we should communicate with the public about advances in AI and their future impact on society. It is a call to action for more AI researchers to become AI educators, creating resources that help teachers and students understand our work. 

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4. Increasing Diversity in Lifelong AI Education: Workshop Report

   https://doi.org/10.1609/aaaiss.v3i1.31263  

   Maher, Mary Lou; Tadimalla, Sri Yash (May 2024, Proceedings of the AAAI Symposium Series)

   AI is rapidly emerging as a tool that can be used by everyone, increasing its impact on our lives, society, and the economy. There is a need to develop educational programs and curricula that can increase capacity and diversity in AI as well as awareness of the implications of using AI-driven technologies. This paper reports on a workshop whose goals include developing guidelines for ensuring that we expand the diversity of people engaged in AI while expanding the capacity for AI curricula with a scope of content that will reflectthe competencies and needs of the workforce. The scope for AI education included K-Gray and considered AI knowledge and competencies as well as AI literacy (including responsible use and ethical issues). Participants discussed recommendations for metrics measuring capacity and diversity as well as strategies for increasing capacity and diversity at different level of education: K-12, undergraduate and graduate Computer Science (CS) majors and non-CS majors, the workforce, and the public. 

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5. An Effectiveness Study of Teacher-Led AI Literacy Curriculum in K-12 Classrooms.

   Zhang, H.; Lee, I.; Moore, K. S (February 2024, Proceedings of the EAAI-24: The 14th Symposium on Educational Advances in Artificial Intelligence.)

   Artificial intelligence (AI) has rapidly pervaded and reshaped almost all walks of life, but efforts to promote AI literacy in K-12 schools remain limited. There is a knowledge gap in how to prepare teachers to teach AI literacy in inclusive classrooms and how teacher-led classroom implementations can impact students. This paper reports a comparison study to investigate the effectiveness of an AI literacy curriculum when taught by classroom teachers. The experimental group included 89 middle school students who learned an AI literacy curriculum during regular school hours. The comparison group consisted of 69 students who did not learn the curriculum. Both groups completed the same pre and post-test. The results show that students in the experimental group developed a deeper understanding of AI concepts and more positive attitudes toward AI and its impact on future careers after the curriculum than those in the comparison group. This shows that the teacher-led classroom implementation successfully equipped students with a conceptual understanding of AI. Students achieved significant gains in recognizing how AI is relevant to their lives and felt empowered to thrive in the age of AI. Overall this study confirms the potential of preparing K-12 classroom teachers to offer AI education in classrooms in order to reach learners of diverse backgrounds and broaden participation in AI literacy education among young learners. 

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