Artificial Intelligence in Education: Foundations, Ethics, and Classroom Application

Description: This professional learning session equips educators with the knowledge and practical strategies needed to both teach artificial intelligence concepts and responsibly integrate AI tools into instruction. Participants will explore foundational AI terminology, machine learning principles, prompt engineering, bias and ethical considerations, and emerging industry trends. Through hands-on experimentation with AI tools and scenario-based analysis, educators will move from understanding AI concepts (DOK1–2) to critically evaluating impact and designing applied AI learning experiences (DOK3–4).

Learning Outcomes:

1.    Explain and differentiate core AI concepts including types of AI, machine learning models, generative AI, prompt engineering, and data bias.

2.    Analyze ethical, societal, and workforce implications of AI, including bias, privacy, misinformation, and career transformation.

3.    Design and implement AI-infused instructional experiences or student projects that incorporate responsible tool use, prompt refinement, and real-world application.