Foundations of AI in Education

This unit establishes core knowledge and pedagogical frameworks for integrating artificial intelligence into K–12 classrooms. Learners explore AI fundamentals (including generative models and machine learning), opportunities and challenges (ethics, equity, privacy), sustainable integration strategies, prompt design, and learning theories that inform AI-driven instruction to prepare for deeper application and policy units that follow.

Learning Objectives

• Analyze opportunities, challenges, and ethical implications of using AI tools in classroom settings, citing specific examples related to bias, privacy, equity, and instructional impact
• Demonstrate foundational knowledge of AI and machine learning concepts (e.g., supervised/unsupervised learning, generative models) and apply that knowledge to evaluate the capabilities and limitations of classroom AI tools
• Apply effective prompt-writing techniques and sustainable AI integration strategies to design at least two lesson-level activities that develop students’ AI literacy, computational thinking, creativity, and align with constructivist, behaviorist, or sociocultural approaches
• Evaluate strategies for preparing students for an AI-driven workforce by creating a classroom plan that fosters a growth mindset, lifelong learning habits, and transferable innovation skills, including assessment and ethical considerations