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The AI4GA project is developing a nine-week elective course called Living and Working with Artificial Intelligence and piloting it in several Georgia middle schools. Since we aspire to educate all students about AI, the course addresses a wide range of student abilities, levels of academic preparedness, and prior computing experience, and leaves room for teachers to adapt the material to their own students' needs and interests. The course content is primarily focused on unplugged activities and online demonstration programs. We also provide small programming projects using AI tools as an option for teachers to incorporate. In this poster we describe lessons learned from initial pilot offerings by five teachers who taught 12 sections of the course totaling 299 students. We present evidence that middle school students can successfully engage with substantive technical content about Artificial Intelligence. 

This article provides an in-depth look at how K-12 students should be introduced to Machine Learning and the knowledge and skills they will develop as a result. We begin with an overview of the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and briefly discuss each of the “Five Big Ideas in AI” that serve as the organizing framework for the guidelines. We then discuss the general format and structure of the guidelines and grade band progression charts and provide a theoretical framework that highlights the developmental appropriateness of the knowledge and skills we want to impart to students and the learning experiences we expect them to engage in. Development of the guidelines is informed by best practices from Learning Sciences and CS Education research, and by the need for alignment with CSTA’s K-12 Computer Science Standards, Common Core standards, and Next Generation Science Standards (NGSS). The remainder of the article provides an in-depth exploration of the AI4K12 Big Idea 3 (Learning) grade band progression chart to unpack the concepts we expect students to master at each grade band. We present examples to illustrate the progressions from two perspectives: horizontal (across grade bands) and vertical (across concepts for a given grade band). Finally, we discuss how these guidelines can be used to create learning experiences that make connections across the Five Big Ideas, and free online tools that facilitate these experiences. 

Over the past year, our AI4GA team of university faculty and middle school teachers have co-designed a middle school AI curriculum. In this poster we share how we used co-design both as a tool for collaboratively developing engaging AI activities and as a mechanism for mutual professional development. We explain our co-design process, give examples of curriculum materials provided to teachers, and showcase several teacher-created activities. We believe this approach to curriculum development centers the lived experiences of teachers and leverages the knowledge and expertise of university researchers to create high quality and engaging AI learning experiences for K-12 students. 

This article provides an in-depth look at how K-12 students should be introduced to Machine Learning and the knowledge and skills they will develop as a result. We begin with an overview of the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and briefly discuss each of the “Five Big Ideas in AI” that serve as the organizing framework for the guidelines. We then discuss the general format and structure of the guidelines and grade band progression charts and provide a theoretical framework that highlights the developmental appropriateness of the knowledge and skills we want to impart to students and the learning experiences we expect them to engage in. Development of the guidelines is informed by best practices from Learning Sciences and CS Education research, and by the need for alignment with CSTA’s K-12 Computer Science Standards, Common Core standards, and Next Generation Science Standards (NGSS). The remainder of the article provides an in-depth exploration of the AI4K12 Big Idea 3 (Learning) grade band progression chart to unpack the concepts we expect students to master at each grade band. We present examples to illustrate the progressions from two perspectives: horizontal (across grade bands) and vertical (across concepts for a given grade band). Finally, we discuss how these guidelines can be used to create learning experiences that make connections across the Five Big Ideas, and free online tools that facilitate these experiences. 

Over the past year, our AI4GA team of university faculty and middle school teachers have co-designed a middle school AI curriculum. In this poster we share how we used co-design both as a tool for collaboratively developing engaging AI activities and as a mechanism for mutual professional development. We explain our co-design process, give examples of curriculum materials provided to teachers, and showcase several teacher-created activities. We believe this approach to curriculum development centers the lived experiences of teachers and leverages the knowledge and expertise of university researchers to create high quality and engaging AI learning experiences for K-12 students. 

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 

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.