Is AI too difficult for a K12 learner? Absolutely not! AI can be taught at a basic and helpful level that K12 learners can benefit from. As educators, one of your objectives would be to future-proof your learners. You want their education to reflect the real world so they can thrive in it. There are times when a technology is helpful in the real-world but may not be suitable to teach young learners. This could be the case for AI in the earlier days. Industries and tech companies were still figuring out how AI can be helpful. At that time, you would require trained professionals or researchers.
Those times are now over! Now, there are many resources and applications suitable even for a young learner. K12 learners can now learn AI at their level and start their future-proofing. These recommended applications or demos are great for an educator to adapt for their lessons. One pre-requesite for using these recommendations is that the learner should have some basic coding knowledge, even if it is block coding.
Machine Learning for Kids
This is one of the earliest resource for learning machine learning. It started as early as 2017 and it is integrated into Scratch and App Inventor. Machine Learning for kids is comprehensive with many worksheets available for download. IBM have made use of Machine Learning for Kids to create a curriculum revolving around their own technology. When you access Scratch 3 from Machine Learning for Kids, you can even find pre-trained coding blocks for use in your projects. These models include face detection, pose detection and Toxicity detection.
Cognimates
Cognimates is a more complex version of Machine Learning for Kids. It is very similar as projects can be built on Scratch, but the key difference is in the model training. Cognimates uses actual professional applications to train its models while Machine Learning for Kids train models within itself. Cognimates act as a good transition for young learners to progress from basics in Machine Learning for Kids to using actual professional applications. in Cognimates.
To use Cognimates, the user must sign up for either Uclassify or Clarifai. Both of these can be used for actual projects. This is suitable when the learner has gone through a basic course, if not the learner has to be at least above 11 years old.
Teachable Machine
Teachable Machine makes it easy to train a model. In a professional environment, models are trained or created with lots of code, and libraries. It is similar to developing a software, where lines of code are written, with lots of testing. With Teachable Machine, training a model is simplified into simple steps. However, the model that is created, assuming the training is done properly, can be imported into a real project.
For teaching, we can skip the importing step, but the simplified starting steps are great for teaching. From Cognimates, the next progression would be Teaching Machine. The learners at this point should have moved beyond block coding to syntax coding.
Emoji Scavenger Hunt
Now we go back to the basics. This application is a game that uses AI. Emoji Scavenger Hunt uses AI to determine objects similar to the emoji it is showing. This resource cannot be a lesson in itself but it is a good introduction activity for young learners. Some concepts of AI can be taught first. Then Emoji Scavenger Hunt can be the next activity to demonstrate how these concepts are used.
Rockpaperscissors.ai
This is another resource for young learners. It works the same way as Emoji Scavenger Hunt. You should be able to find many rock paper scissors AI game online. This activity is usually used in tandem with Emoji Scavenger Hunt to highlight AI concepts. Depending on the time of the lesson, this activity can be included in your teaching.
Conclusion
Now is a good time for young learners to get started on understanding AI. AI will be part of their lives and having an awareness will be beneficial. These resources can also be integrated into your own subject lesson to make your lessons interesting and for learners to see how AI can impact different areas.
What do you think? Should kids learn AI?
