NSF K-12 AIED Workshop 2

Since the first workshop held in 2019, there has been growing research into how to help the K-12 student population develop a clear understanding of AI and its societal impact. At the same time, interests in introducing AI education in K-12 classrooms are growing at unprecedented pace that has garnered attention from state boards of education and policy makers. To understand the state-of-the-art, share findings within this new community, and identify research gaps, we invited researchers who are currently engaged in K-12 AI education research to a 2-day virtual workshop. At the workshop, the participants engaged in breakout groups as well as whole group discussions to share their insight into questions on AI learning progression through different grade bands, integration of AI education into K-12 curriculum, research gaps that need to be addressed, and AI ethics education. Participants also participated in 2 rounds of small group discussions. Each group consisted of researchers from different project teams. Participants were assigned to different groups for each round of the discussion. After each small group discussion, all participants rejoined as a group to reflect upon the key takeaways from the group they represented.

The two-day workshop agenda is here.

A total of 30 researchers who are currently engaged in K-12 AI education research participated in the workshop.

A report on workshop 2 findings is available here.

The series of workshops aim to build an interdisciplinary research community to address the critical challenge of creating a national K-12 AI education strategy. The workshops include leading members of the AI research community, the education research community, AI industry, and educational practitioners. The workshops aim to play a central role in introducing researchers from across AI and education to each other to establish the connections that are essential to the success of a national K-12 AI education initiative. Collectively, leaders in these fields will develop a research agenda on best practices for AI education for K-12 student populations. Such a research agenda can have broad societal implications ranging from science, technology, engineering, and mathematics applications in every sector of the economy to workforce development and national security.