Teaching artificial intelligence in K–12 classrooms: a scoping review

The teaching of artificial intelligence (AI) has increasingly become a topic of investigation among educational researchers. Studies of AI education have predominantly focused on the university level; less attention has been paid to teaching AI in K–12 classrooms. This study synthesised empirical studies on K–12 AI education, with the aims of understanding how AI has been taught at the K–12 level and informing future AI curriculum development. We analysed 21 articles in terms of their AI curriculum design and the learning effects. The results indicated that (1) most of the studies aimed to teach students to understand AI knowledge at the K–12 level; (2) their teaching content covered a variety of AI-related topics, such as machine learning and deep learning; (3) different teaching approaches were used in AI classrooms, including inquiry-based learning, project-based learning, and game-based learning; (4) three measurement approaches, namely surveys, questionnaires and assessments, were commonly adopted to evaluate learning outcomes; and (5) participating in AI curricula enabled students to learn the basic functions of AI, apply AI knowledge, evaluate and create AI applications, and understand AI-related ethical issues. Based on the findings, we offer pedagogical suggestions and discuss directions for future research.