The first of the Grand Challenges identified in the Government’s Industrial Strategy is about Artificial Intelligence. One of the things that these challenges highlight is the UK’s need for skills in these key areas.
To that end, STEM Learning and the Department for Business, Energy and Industrial Strategy have created the “Grand Challenges – Our Futures” programme to improve young people’s knowledge of the STEM skills identified in the Government’s Industrial Strategy Grand Challenges.
Last week, STEM Learning announced a set of new free resources to support teaching in these key areas.
The Artificial Intelligence resources include three different packages aimed at students of different ages.
Level 1
The Level 1 resources are aimed at 10-12 year olds, and include some Scratch projects from Machine Learning for Kids, together with teaching notes, and presentation materials.
Using a visual based programming language, students will develop a program that is capable of using machine learning, they will train, develop and test the program to enable a user to enter a description of how they’re feeling, and the program will automatically be able to detect the type of mood the user is in.
Machine learning programs are also able to work with other data types including images, students will explore how programs can be developed to categorise images by training, developing and testing a program to identify the characteristics of different objects.
Having developed example machine learning programs, students will reflect upon the benefits and drawbacks of using this in society. They will use this information along with their programming work to present to the rest of the group.
Level 2
The Level 2 resources are aimed at 12-14 year olds, and include a Scratch project from Machine Learning for Kids, together with teaching notes, presentation materials, prompt cards, and practical “unplugged” activities.
Using a visual based programming language, students will develop a program that could be used by someone on holiday to suggest local activities on a map based upon their preferences, students will train, develop and test the program to ensure the most suitable activities are suggested.
Machine learning and artificial intelligence systems are being heavily invested upon within our healthcare system. There are still many questions that are commonly asked around the ethics of using such systems, students will explore how these programs are being adopted in healthcare to improve chances of survival etc. Students will use their knowledge to explore and discuss in more depth the arguments for and against its use. Working in groups, students will act out a court scene scenario posing their arguments for or against the use of AI in our healthcare systems.
Level 3
The Level 3 resources are aimed at GCSE – A-Level students, and include a Python project from Machine Learning for Kids, together with teaching notes, and presentation materials.
Using the text programming language Python, students will develop a program that could be used by someone on holiday to suggest local activities on a map based upon their preferences, students will train, develop and test the program to ensure the most suitable activities are suggested. This activity will also draw upon prior programming skills.
This is all very exciting to see. I’m very proud to have been able to contribute to this – I put the Creative Commons license on all of the ML worksheets I’ve written to enable exactly this sort of thing. I’m looking forward to seeing what schools produce with it!
Also…
While I’m sharing fantastic uses of Machine Learning for Kids, there are two other recent ones I should point out:
The Raspberry Pi Foundation are producing a series of free machine learning project resources based on Scratch projects from Machine Learning for Kids.
Technovation are running their AI Family Challenge again, producing a range of resources to help families create new and original projects with Machine Learning for Kids.
There are so many others I could mention, so I’ll just share some links below…