How LLMs Really Work: Patterns, Not Memory | Classroom Lesson (K–12)

Learn how to teach students how large language models (LLMs) really work—by recognizing patterns, not storing memories. In this lesson, students use skip counting and pattern recognition to understand how AI systems make predictions. Then, they program Ozobots to complete patterns, modeling how language models generate responses based on learned sequences. This hands-on activity helps students move beyond common misconceptions and build a clear, foundational understanding of how AI works. In this lesson, students will: – Understand that AI models rely on patterns, not memory or “thinking” – Use skip counting to identify and extend patterns – Program Ozobots to predict and complete sequences – Connect math concepts to real-world AI systems Large language models like ChatGPT do not “remember” information the way humans do—they generate outputs by predicting patterns based on training data. This lesson is ideal for STEM, math, and computer science classrooms introducing AI literacy in a clear and approachable way. 👉 Explore the full lesson: https://classroom.ozobot.com/lessons/lnLr9tisvERaO9579mU0vDmQpB 👉 Discover more AI lessons: https://classroom.ozobot.com/ This video is part of a K–12 AI literacy and coding lesson series for classrooms. #AILiteracy #CodingForKids #STEMEducation #EdTech #Ozobot