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A short class with Sarah and her students. The other ways are under More.
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Welcome, class! Today, we’re going to learn about using AI in a really fun way with a gesture recognition project using Scratch. Can anyone guess what gesture recognition involves?
I think it means the computer can understand what we do with our hands!
Exactly! We can use it to control a Scratch sprite. We will first train the model to recognize different gestures. What do you think we need to do that?
Maybe we need to show the computer different hand movements?
That's right! We collect data of different gestures. This step reminds us of the 'D' in AI: Data collection. Let’s remember it by saying 'Data Defines Decision'.
So we collect data, and then we can make the sprite do something when it sees those gestures?
Yes! Once we gather enough data, we train our model. By the end of this project, you’ll be able to see how your hand movements can control your sprite. Let’s outline the steps we need to take together!
This sounds really cool!
Great enthusiasm! Let's summarize. We learned the importance of data collection for teaching AI systems. Remember: 'Data Defines Decision'. Next, we will start our activity!
Welcome back! Now, we’ll look at a project where a robot reacts to sounds. How do you think we can use AI to recognize sounds?
By teaching it which sounds to listen for?
Exactly! We'll train an AI model to listen to different sounds, like claps or whistles. Sound recognition allows us to classify audio inputs, similar to how gesture recognition works. Anyone familiar with the term 'classification'?
Isn't that when the AI decides which category something belongs to?
Correct! Classification helps the AI to make decisions based on inputs. Can anyone think of a practical application of this concept?
Maybe in smart assistants like Siri or Google Assistant?
Exactly how it works! Now, let's summarize what we have learned: AI can classify sounds and respond in real-time. It'll be fun to see your robots react live!
To make a sprite pose, show your hand—, AI will understand!
Imagine a robot that dances. Each clap tells it to jump; each whistle makes it spin! This is how sound classification brings your projects to life!
For gesture projects, remember: G for Gesture, C for Control, and A for AI.
AI: Actions Interpreted - because that's what our models do!
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What is Teachable Machine?
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What is gesture recognition?
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What does sound classification do?
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This section explores example activities using AI tools to engage students in hands-on learning.
The section highlights engaging Example Activities that utilize AI-based tools like Scratch and Blockly to teach fundamental AI concepts through interactive projects. The activities illustrate concepts such as gesture recognition and sound responses, making AI accessible without prior coding experience.
In this section of Chapter 12, we delve into practical activities designed to illustrate the fun and tangible applications of Artificial Intelligence (AI) using visual programming tools like Scratch and Blockly. These platforms allow students to engage with AI concepts without the need for extensive coding skills. Each activity presents a unique opportunity for learners to grasp core ideas while creating engaging projects.
Training Gesture Recognition Models: Students can create a model that recognizes hand gestures which can then be used to control a Scratch sprite. This activity emphasizes basic AI concepts such as data collection and model training, providing a dynamic way to understand input/output systems in programming.
Sound-based Robot Interactions: Participants can design a robot that reacts differently depending on various detected sounds. This showcases the AI principle of classification and introduces students to audio recognition, expanding their understanding of sensory data interpretation and response mechanisms.
These activities not only foster creativity and critical thinking but also bridge the gap between theoretical learning and real-world application of technology.