As the need for teaching Artificial Intelligence (AI) for K-12 is increasing, discussions on what competencies teacher should have for effective teaching of AI is overlooked. In this work, we determine what teacher competencies are necessary for improving the teaching and learning of AI for K-12 with Technological Pedagogical Content Knowledge (TPACK) framework. First, we identify current AI education resources and investigate the core foundations of AI taught to K-12. Based on the findings, we propose teacher competency for K-12 AI education by analyzing AI curricula and resources using the TPACK framework. We conclude that teachers who teach AI to K-12 students require TPACK to construct, prepare an environment, and facilitate project-based classes that solve problems using AI technologies.
Bibliographical noteFunding Information:
The National Science Foundation (NSF) of the United States launched AI4K12 Initiative to support setting up national guidelines for K-12 AI education . AI4K12 is jointly sponsored by NSF, Association for the Advancement of Artificial Intelligence (AAAI), and Computer Science Teachers Association (CSTA). The motivation of the AI4K12’s K-12 AI curriculum guideline are: The K-12 AI curriculum guideline is categorized into four grade bands: K-2, K3-5, K6-8, and K9-12. The guideline also includes Five Big Ideas in AI, an organizing framework covering core concepts of AI . The Five Big Ideas in AI are: The AI4K12 Initiative further provides major concepts and related learning activities for each idea of the Five Big Ideas in AI. Table describes the details.
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- AI education
- South Korea
- Teacher competency
ASJC Scopus subject areas
- Artificial Intelligence