Designing AI Learning Experiences for K-12: Emerging Works, Future Opportunities and a Design Framework

TL;DR

This paper reviews current K-12 AI literacy education, analyzes existing resources, and proposes a design framework to guide future development of effective AI learning experiences for young students.

Contribution

It provides an organized overview of AI literacy competencies, identifies gaps, and introduces a conceptual framework for designing K-12 AI education tools and curricula.

Findings

Core AI literacy competencies are effectively applied in existing resources.

A chart was created to help educators find suitable AI learning resources.

Future design guidelines and a conceptual framework were developed for K-12 AI education.

Abstract

Artificial intelligence (AI) literacy is a rapidly growing research area and a critical addition to K-12 education. However, support for designing tools and curriculum to teach K-12 AI literacy is still limited. There is a need for additional interdisciplinary human-computer interaction and education research investigating (1) how general AI literacy is currently implemented in learning experiences and (2) what additional guidelines are required to teach AI literacy in specifically K-12 learning contexts. In this paper, we analyze a collection of K-12 AI and education literature to show how core competencies of AI literacy are applied successfully and organize them into an educator-friendly chart to enable educators to efficiently find appropriate resources for their classrooms. We also identify future opportunities and K-12 specific design guidelines, which we synthesized into a conceptual framework to support researchers, designers, and educators in creating K-12 AI learning experiences.