In celebration of AI Literacy Day, we’re focusing on aligning the rapid evolution of artificial intelligence and the needs of today’s students. Beyond just exposure to AI technology, students need the skills to understand, question, and apply it. Teaching AI literacy in K–12 classrooms helps students build critical thinking, problem-solving, and digital literacy skills while preparing them for an AI-driven world. The good news: you don’t need a background in computer science to get started. With the right lessons and tools, educators can introduce AI concepts in ways that are engaging, accessible, and aligned to classroom learning goals. In this post, we’ll explore classroom-ready AI Ozobot lessons that help students move from curiosity to real understanding.
Ethics Lab: AI on Trial
Step into the role of an AI Ethicist! Students will investigate how AI can make biased decisions, propose improvements, and use Color Codes to demonstrate their evaluation of AI decisions with Ozobot. Download the Ethics Lab: AI on Trial AI lesson here.
Academic Standards:
NGSS.3-5-ETS1-3, CSTA.1B-IC-20, ISTE.2.b
AI Literacy Competency: Evaluate – Evaluate whether AI outputs should be accepted, revised, or rejected, AI Literacy Competency: Explain – Explain how AI could be used to amplify societal biases
Invisible Inputs: Analyzing Bias in AI Healthcare Tools
Students investigate how biased proxy data led a healthcare algorithm to underestimate the needs of certain patient groups. They analyze the case, debate fairness, and use Color Codes to model how design choices affect equity in AI. Download the Invisible Inputs: Analyzing Bias in AI Healthcare Tools AI lesson here.
Academic Standards
CSTA.3A-IC-25, ISTE.2.b, NGSS.HS-ETS1-3
AI Literacy Competency: Evaluate – Evaluate whether AI outputs should be accepted, revised, or rejected, AI Literacy Competency: Explain – Explain – Explain how AI could be used to amplify societal biases
Prediction Pro
Students explore how LLMs learn by predicting Ozobot’s next action. Then, programming Ozobots to follow patterns and act out story paths, connecting repetition and prediction to the way language models are trained. Download the Prediction Pro AI lesson here.
Academic Standards
CSTA.2-AP-13, CSTA.2-AP-16, CCSS.ELA-LITERACY.W.6.2, NGSS.MS-ETS1-2
AI Literacy Competency: Recognize – Recognize AI’s role and influence in different contexts
Patterns Not Memory: How LLMs Work
Students use skip counting as a way to identify patterns and make predictions. Then, they program Ozobot to complete a pattern to understand how LLMs work. Download the Patterns Not Memory: How LLMs Work AI lesson here.
Academic Standards
NGSS.3-5-ETS1-2, CSTA.1B-AP-09, CCSS.MATH.CONTENT.3.OA.D.9
AI Literacy Competency: Recognize – Recognize AI’s role and influence in different contexts.
Think Like A Model: A Large Language Model
Students will run a program to simulate training an LLM and make a prediction about the next color. Students will write the beginning of a short story, then exchange with a partner who will finish the story and design a pathway for Ozobot to follow. Download the Think Like A Model: A Large Language Model AI lesson here.
Academic Standards
CSTA.3B-AP-08
