Exploring the AI competencies of elementary school teachers in South Korea

Although the importance of K–12 artificial intelligence (AI) education grows, the lack of teacher readiness hinders the integration of AI in schools. To address this issue, this study aimed to explore South Korean elementary school teachers' experiences teaching AI curricula and examine their competencies. A survey and interviews were conducted with 67 elementary school teachers who have been working in AI-leading schools in South Korea. The results indicated that teachers were least confident in content knowledge, followed by technological knowledge and pedagogical knowledge relevant to AI. Additionally, interviews with 13 teachers revealed five themes regarding AI education: (1) emphasizing the importance of instructional design in AI education; (2) redesigning the learning environment to promote learning experiences; (3) lowering teaching anxiety by acknowledging the limitations of content knowledge; (4) extending AI education based on computer science (CS) principles; and (5) acquiring literacy in codes, data, AI technologies, and ethical issues. Based on the findings, 22 AI competencies for elementary school teachers were derived and categorized based on the technological pedagogical content knowledge (TPACK) framework. The competencies provide a practical framework for teachers to acquire the necessary knowledge and skills for AI education. The study contributes to understanding AI teaching practices in South Korea by revealing teachers’ perspectives on and identifying the essential competencies for practicing AI education.