Digital Zoologists: Researching with the LLM
Become a digital zoologist by using the LLM block to research animals and create a field report! Test what the LLM can accurately answer by asking a variety of questions with different output types to program Ozobot’s behavior based on the responses.
AI-Powered Population Maps
Use the LLM block to collect real-world population and land area data from 10 different countries! Students will calculate population density, rank countries from most to least crowded, and create an AI-powered population map.
Prominent Black Engineers and Scientists
Students will choose an influential Black scientist and/or engineer, research their lives, and create a biographical timeline for Ozobot to follow.
Slot Car Race Track
Rev up your engines and get ready to code! Design a Blockly program to navigate an Ozobot slot car around a race track. Race across the finish line using line navigation, timing, and light effects blocks!
The Interactive Flowchart Part 1 of 3
Students are introduced to structured flowcharting in an interactive lesson, followed by applying flowcharting to an original scenario of their choice. Originally written by Dr. Richard Born, Assoc Professor Emeritus, Northern Illinois University.
Dizzy Evo OzoBlockly Challenge
Using OzoBlockly, students program Evo to zigzag as it traverses a circular room without ever touching the walls.
Evo Demonstrates Linear and Binary Searches
Provided OzoBlocky programs simulate linear and binary searches on Ozomaps. Evo then searches for values interactively inputted by students.
OzoBlockly Challenge: Evo Loops-the-Loop
Students design an OzoBlockly program making Evo loop-the-loop a specified number of times. At the finish, Evo speaks the total time for the loops.
Ozobot’s Color Quest (Part 3 of 5)
Learn how to use math operator and variable blocks to build a robot calculator. Then utilize your knowledge to construct a points tracker for the Color Quest Game!
Hockey Simulator Level 1 Movement
Level 1 of Hockey Simulator demonstrates the complete hockey program, then teaches how to build the autonomous movement using conditionals, loops, and sensors. This lesson is part 1 of a 5-lesson series.