Teaching Tech to Talk: K-12 Conversational Artificial Intelligence Literacy Curriculum and Development Tools

TLDR

The growing prevalence of smart devices makes it essential to teach students how conversational AI agents function and their societal implications. The study evaluates a MIT App Inventor–based Conversational Agent Interface and its workshop curriculum against eight AI competencies from the literature. The authors assessed the interface and curriculum by measuring alignment with the eight competencies and collected feedback from nine teachers and 47 students. Students demonstrated understanding of all eight competencies, but AI ethics and machine learning proved most challenging, leading the authors to recommend emphasizing these topics in future curricula.

Abstract

With children talking to smart-speakers, smart-phones and even smart-microwaves daily, it is increasingly important to educate students on how these agents work—from underlying mechanisms to societal implications. Researchers are developing tools and curriculum to teach K-12 students broadly about artificial intelligence (AI); however, few studies have evaluated these tools with respect to AI-specific learning outcomes, and even fewer have addressed student learning about AI-based conversational agents. We evaluated our Conversational Agent Interface for MIT App Inventor and workshop curriculum with respect to 8 AI competencies from the literature. Furthermore, we analyze teacher (n=9) and student (n=47) feedback from workshops with the interface and recommend that future work (1) leverages design considerations to optimize engagement, (2) collaborates with teachers, and (3) addresses a range of student abilities through pacing and opportunities for extension. We found evidence for student understanding of all 8 competencies, with the most difficult concepts being AI ethics and machine learning. We recommend emphasizing these topics in future curricula.