From Human Motion to Intelligent Machines: Teaching Physical AI Through Science, Engineering, and Robotics
How do you make AI tangible for students? In this workshop, explore Physical AI Learning Labs that connect science, engineering design, robotics, sensing and evidence-based reasoning. Starting with simple motion examples, you will see how motion can be represented as data, translated into mechanism designs, tested with low-cost prototypes and revised using sensor evidence. Along the way, you will expand your own content knowledge of AI-enabled physical systems and experience research-based strategies such as modeling, retrieval, reflection and iterative design that build technological literacy through rigorous, developmentally appropriate STEM experiences. You will leave with adaptable lesson ideas, assessment prompts and inclusive strategies to support diverse learners, including English language learners, in safe, equitable, hands-on classrooms, ready to help students understand how intelligent machines sense, move and respond to the physical world. All workshops are BYOD and require All Access or Session + Registration to attend.
Speakers
Access Type
All-Access or Session+ Registration Permitted (Pre-registration required.)
Content Topic
STEM/STEAM
Curriculum Area
Computer Science (Coding/Robotics/etc.)
Session Type
Workshops
Education Challenges
Student Engagement
EdTech Product
CTE,Upskilling & Credential Technology,Future Learning Technology (STEAM),Student Learning Technology