Description
Description: This beginner AI module explains machine learning ideas using kid-friendly tools that run in a browser. Students collect tiny image or sound samples and train a model to recognize simple categories. They connect the model to Scratch so sprites react to live camera or microphone input in playful projects. Lessons emphasize responsible data choices and what makes a training set fair or biased. Students compare good vs. noisy samples and see how results change when they add more examples. They learn that AI has limits and should be tested carefully before sharing. A debugging lab shows how to evaluate false positives and adjust thresholds. Privacy practices include working with local files and turning off the camera when not in use. Showcase prompts encourage building interactive posters or vocabulary helpers for other classes. By the end, students can explain AI in plain language and demonstrate a working prototype safely.
Format: Guided videos + Scratch templates + model training worksheet + safety checklist
Duration: 2–3 weeks (five 45–60 minute lessons)
What You’ll Learn: Basics of ML, dataset quality, classification, live inputs, testing, privacy and safety
Target Audience: Grades 6–9 students curious about AI with a creative, hands-on approach
