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Rapid advancements in artificial intelligence (AI) necessitate changes in what AI content is taught 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. 

Neuron Sandbox is a browser-based tool that helps middle school students grasp basic principles of neural computation. It simulates a linear threshold unit applied to binary decision problems, which students solve by adjusting the unit's threshold and/or weights. Although Neuron Sandbox provides extensive visualization aids, solving these problems is challenging for students who have not yet been exposed to algebra. We collected survey, video, and worksheet data from 21 seventh grade students in two sections of an AI elective, taught by the same teacher, that used Neuron Sandbox. We present a scaffolding strategy that proved effective at guiding these students to achieve mastery of these problems. While the amount of scaffolding required was more than we originally anticipated, by the end of the exercise students understood the computation that linear threshold units perform and were able to generalize their understanding of the worksheet’s solve for threshold strategy to also solve for weights. 

There are many initiatives that teach Artificial Intelligence (AI) literacy to K-12 students. Most downsize college-level instructional materials to grade-level appropriate formats, overlooking students' unique perspectives in the design of curricula. To investigate the use of educational games as a vehicle for uncovering youth's understanding of AI instruction, we co-designed games with 39 Black, Hispanic, and Asian high school girls and non-binary youth to create engaging learning materials for their peers. We conducted qualitative analyses on the designed game artifacts, student discourse, and their feedback on the efficacy of learning activities. This study highlights the benefits of co-design and learning games to uncover students' understanding and ability to apply AI concepts in game-based learning, their emergent perspectives of AI, and the prior knowledge that informs their game design choices. Our research uncovers students' AI misconceptions and informs the design of educational games and grade-level appropriate AI instruction. 

Middle School students in the United States are exposed to an unprecedented number of AI-driven consumer products. This exposure demands that educators help students develop their personal understandings of these technologies to engage with them responsibly. Designing age-appropriate AI curricula for middle school students calls for collaboration and partnership between computer and learning scientists, as well as middle school teachers. Over a 3-year period, we co-designed and successfully implemented an AI education curriculum across 9 geographically and economically diverse schools, offering it to a total of 1551 students. Drawing from our analyses of the curriculum and teacher and student experiences, we propose an effective format for teaching, assessing, and implementing fundamental AI education for middle school settings in the United States. Our research also highlights the value of empowering teachers through co-design; enriching their professional development and improving students’ AI literacy. 

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. 

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. 

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.