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Fostering public AI literacy has been a growing area of interest at CHI for several years, and a substantial community is forming around issues such as teaching children how to build and program AI systems, designing learning experiences to broaden public understanding of AI, developing explainable AI systems, understanding how novices make sense of AI, and exploring the relationship between public policy, ethics, and AI literacy. Previous workshops related to AI literacy have been held at other conferences (e.g., SIGCSE, AAAI) that have been mostly focused on bringing together researchers and educators interested in AI education in K-12 classroom environments, an important subfield of this area. Our workshop seeks to cast a wider net that encompasses both HCI research related to introducing AI in K-12 education and also HCI research that is concerned with issues of AI literacy more broadly, including adult education, interactions with AI in the workplace, understanding how users make sense of and learn about AI systems, research on developing explainable AI (XAI) for non-expert users, and public policy issues related to AI literacy. 

This paper examines the use of collaborative curriculum design (co-design) as a strategy for supporting teacher professional learning and the implementation of an inclusive middle school computer science and digital literacy (CSDL) curriculum in three urban school districts. The curriculum is focused on students developing mobile apps that provide social and community good. The second year of the project has been dedicated to developing and piloting curriculum resources that support remote learning and culturally relevant pedagogy while the partner districts switched to remote and hybrid instructions. This study explores teachers’ professional learning experiences in the collaborative design of curriculum materials and piloting the curriculum at their own classrooms. The paper includes analysis of three data sets: (1) co-design meeting notes and teacher reflections; (2) semi-structured interviews with teachers who co-designed and piloted the curriculum; (3) student pre- and post-survey responses on their attitude and interest in learning CSDL. Preliminary results indicate that the co-design approach supplemented with one-on-one coaching has not only facilitated the curriculum development process but also fostered professional learning and collective capacity building for implementing the project curriculum in the partner districts. Findings from student surveys show that students perceived their understanding of, and interest in computer science and creating apps were slightly improved, regardless of gender. 

This poster shares our experience of engaging middle school teachers in a collaborative design of a computer science and digital literacy (CSDL) curriculum through a researcher and practitioner partnership (RPP) among two public universities and three urban school districts in the Northeast USA. The project used the co-design approach to facilitate curriculum development and foster professional learning. In this poster, we introduce the co-design process, the developed curriculum, and teachers' professional learning experiences. Preliminary results indicate that the co-design approach supplemented with one-one-on coaching has not only facilitated the curriculum development but also fostered professional learning and collective capacity building for CS education. 

This pilot study explores the impact of the CS Pathways professional development (PD) program on the teachers' self-efficacy in teaching a middle school computer science and digital literacy (CSDL) curriculum. The main goal of the study is to investigate the attributes that describe the teachers' self-efficacy after their first-year participation in the PD. A total of 19 middle school teachers from two states, NY and MA, attended the CS Pathway PD program and completed the end-of-year survey pertaining to self-efficacy in CSDL; more than half accepted the interview to help further understand their perceptions (n=10). Principal Component Analysis (PCA) is applied to study the attributes of the teachers' self-efficacy. The preliminary results capture teachers' self-efficacy patterns, which inform the PD and indicate its effectiveness and challenges. 

This paper presents an experience report from an NSF-funded researcher-practitioner partnership (RPP) project. Based on a collaboration among two public research universities and three urban school districts in the Northeast USA, the goal of the project is to establish an institutionalized middle school computer science curriculum in the districts. The CS curriculum incorporates digital literacy skills as an integral aspect of learning computer science, and is based on students developing mobile apps that provide social and community good. Here, we share our professional learning process during the project's first year, which had been developed iteratively and dynamically adjusted to a remote format in response to exigencies of Spring 2020. The paper includes analysis of three data sets from teacher-participants: (1) their questions about the nature of the project, which we categorized into three levels: project, district and teacher levels. These questions bridge the visions and knowledge among different groups of the project partners; (2) analysis of semi-structured interview conversations with more than half of the teacher-participants; and (3) teacher survey responses. Our findings include two recommendations: that RPP projects elicit teacher questions to illuminate the three levels identified, and use strategies that engage teachers in designing a professional learning process for teaching computer science. 

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