Introduction to Color Codes 09: Skills Check 2 (Grades K-2)
Students apply their understanding of Timers and Line Switch Color Codes to program Ozobot to complete a scavenger hunt.
Introduction to Color Codes 08: Counters
Students will learn Color Codes to program Ozobot to count three things: intersections, turns at intersections, and changes in path color. Students will also learn how to use the Point Counter Color Codes.
Introduction to Color Codes 06: Timers
Students will learn Color Codes to program Ozobot to run and stop following a timer. They will also observe how speed and time are related when programming Ozobot to complete a task.
Introduction to Color Codes 04: Direction
Students will explore the random choice Ozobot makes at intersections when not programmed to turn a certain direction. They will also program their bot to turn a specific direction at intersections and gain experience using u-turn codes.
Introduction to Color Codes 03: Special Moves and Win
Students will learn how to draw Color Codes to program Ozobot to complete special moves.
Introduction to Color Codes 02: Speed
Students will learn how to draw Color Codes to program Ozobot to change speed.
Introduction to Color Codes 01: Basic Training
Students will discover the basics about how to use Ozobot: turning on/off, calibrating, drawing lines, and programming with Color Codes.
Coral Inhabitants
Become a marine scientist! Build an interactive coral reef to explore how ocean animals feed and shelter. Program Ari to mimic an ocean creature’s journey, track coral visits, and analyze your data to compare results.
Think Like a Model: 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.
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.