Machine Learning Hands on with Google Teachable Machine
Part Four in a Series on AI and Computer Science Literacy.
In the first three articles of this series, we laid the groundwork for integrating artificial intelligence (AI) and computer science (CS) literacy in middle and high school curriculum. We discussed the growing importance of these fields and how foundations in programming logic and physical computing can set students up for success.
Now in this fourth installment, we bring these key concepts together as we explore practical ways to teach core AI skills with accessible tools. Specifically, we will utilize Google’s Teachable Machine platform to create an engaging 60-minute lesson for high school and middle school students who have at least prior experience with block-based coding.
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Teachable Machine is a web-based, no-code AI experience from Google that allows users to train basic image, pose, and audio machine learning models right in the browser. With its intuitive drag-and-drop interface, it serves as an ideal entry point for students to grasp AI and machine learning fundamentals through hands-on experimentation.
This 60-minute lesson plan introduces high school and middle school students with prior coding experience to artificial intelligence concepts and applications using the Teachable Machine platform. Students will discuss AI ethics, explore the Teachable Machine site, and then use the tool to train an image recognition model to identify cats and dogs. The hands-on activity takes students through the full machine learning pipeline - gathering training data, building and evaluating models, and refinement. By the end, students will have built a basic AI application, learned about bias in algorithms, and reflected on the impacts of AI, all catalyzing their passion in this emerging field.
By engaging firsthand with the machine learning process through Teachable Machine, students will gain critical knowledge of how AI algorithms function while unleashing their creativity. They will also encounter important ethical considerations surrounding bias, fairness, and responsible innovation.
Equipping the next generation with AI skills for the future starts small but practical. In this article, we will detail a lesson to ignite students’ passion in artificial intelligence using Teachable Machine’s intuitive platform. Let’s dive in.
60-Minute Lesson: Introduction to AI and Teachable Machine
This lesson introduces high school/middle school students to the world of Artificial Intelligence (AI) using the user-friendly Teachable Machine platform. It assumes students have basic coding experience with block-based tools like Scratch or Blockly.
Learning Objectives:
Define AI and its different types.
Explore real-world applications of AI.
Understand the ethical considerations of AI.
Get hands-on experience with Teachable Machine to build a simple image recognition model.
Lesson Materials:
Computers with internet access
Webcams (optional)
Teachable Machine website (https://teachablemachine.withgoogle.com/train)
Images for training (https://teachablemachine.withgoogle.com/models/o9D1N5TN/)
Lesson Outline:
Introduction (10 minutes):
Start by asking students what they know about AI.
Show a short video:
Discuss the different types of AI (e.g., machine learning, deep learning) and their applications in various fields (e.g., healthcare, transportation, education).
Discuss the ethical considerations of AI:
Bias and fairness in algorithms
Privacy and security concerns
The impact of AI on jobs and the economy
Teachable Machine Introduction (10 minutes):
Introduce Teachable Machine: A user-friendly platform that allows anyone to build and train AI models without coding.
Explore the Teachable Machine website:
Show the different types of models you can build (image, sound, pose recognition).
Explain the basic steps of training a model:
Collect data (images, sounds, poses)
Train the model
Test and refine the model
Building an Image Recognition Model (30 minutes):
Task: Train Teachable Machine to recognize cats and dogs.
Step 1: Data Collection:
Show students the pre-selected images of cats and dogs.
Explain the importance of having a balanced and diverse dataset.
Step 2: Model Training:
Guide students through the Teachable Machine interface.
Explain the different buttons and functionalities.
Train the model with the collected data.
Step 3: Testing and Refinement:
Have students test the model on new images of cats and dogs.
Discuss the accuracy of the model and how to improve it.
Refine the model by adding more data or adjusting training parameters.
Wrap-up (10 minutes):
Recap the key takeaways of the lesson.
Encourage students to explore Teachable Machine further and experiment with different types of models.
Pose questions for reflection:
How do you think AI will impact your future?
What are some creative ways AI can be used to solve problems?
How can we ensure that AI is developed and used ethically?
Assessment:
Observe student participation during activities and discussions.
Evaluate students' understanding of AI concepts through short quizzes.
Assess students' practical skills by reviewing their completed image recognition model.
Out of class: have the students answer a few open ended questions or provide a simple writing prompt for a 150-300 word writing assignment.
This 60-minute lesson provides a basic introduction to AI and Teachable Machine for high school/middle school students. By following the lesson outline and utilizing the provided resources, students will gain a solid foundation in AI concepts and hands-on experience with a user-friendly AI platform.
Additional Resources:
Teachable Machine website: https://teachablemachine.withgoogle.com/train
Teachable Machine tutorials: https://teachablemachine.withgoogle.com/
AI4K12: https://ai4k12.org/
Additional AI Classroom Tools and Tips:
Tools
TensorFlow Playground (by Google): This interactive platform allows students to explore various aspects of machine learning in a visual and engaging way. They can build simple neural networks, visualize data, and understand the training process. (Free)
Artificial Intelligence (AI) Education for Teachers (by Coursera): This online course offered by Macquarie University and IBM on Artificial Intelligence (AI) education for teachers. It discusses what AI is and why it is important for teachers to understand. The course also covers how to embed AI into the curriculum and how to teach students critical thinking skills. Some of the important points from this article are that AI is being used in many different fields and that it is important to ensure that AI is used ethically.
Tips
Encourage students to learn about the ethical implications of AI.
Discuss the potential benefits and risks of AI in various contexts.
Help students develop critical thinking skills to evaluate AI-generated content.
Consider inviting guest speakers from the field of AI to talk to your students.
Participate in online communities and forums to connect with other AI educators.
By using these free tools and resources, middle and high school teachers can effectively teach AI concepts to students and prepare them for the future of technology. Remember, hands-on experiences and engaging resources are key to sparking students' interest in AI and encouraging them to explore this exciting field further.
Conclusion
Through this four-part series, we have laid out the rationale and roadmap for integrating artificial intelligence literacy into middle and high school curriculums. We discussed the growing relevance of AI and computer science skills and provided practical guidance on establishing student competencies, from foundational programming logic to real-world AI applications using tools like Teachable Machine. Equipping students with both the knowledge and ethical grounding to participate in an AI-powered future cannot wait. We hope this series has sparked ideas and conversations at your school about AI education. Start small but start concrete. Empower your students today to become the innovative but responsible leaders of tomorrow’s AI systems and solutions.