Most of us interact with forms of artificial intelligence (AI) and machine learning on a daily basis, from image and voice recognition on social media, online shopping platforms and virtual personal assistants.
These technologies are already ingrained in our society and our day-to-day lives.
But AI and machine learning aren’t only making our lives easier, these technologies are also helping to solve some of today’s big challenges, whether it be diagnosing medical conditions more effectively or breaking down language and communications barriers with speech recognition and translation software.
As we look to the future, it is likely the capabilities of these technologies will become even more sophisticated and intertwined with our daily routines, paving the way for exciting innovations in our lives and society in general.
However, for this to happen we need a generation well-versed in the complexities and inner workings of AI and machine learning. Project based learning (PBL) can provide an easily accessible and hands-on way for young people to get to grips with these technologies.
And because this technology is already having a wide-reaching and varied impact on our lives, there are lots of opportunities to make lessons intuitive and inclusive to ensure all pupils feel able to engage with the subject, not just those who are more likely to naturally engage with science subjects.
AI – Where to start teaching
AI and machine learning can feel like a bit of a nebulous subject area, which is why it is important to clearly define the terms from the very beginning. For example, explain that:
- Artificial intelligence is an umbrella term that refers to a suite of technologies in which computer systems are programmed to exhibit complex behaviour, when acting in conditions of uncertainty
- Machine learning is a technology that allows computers to learn directly from examples and experience in the form of data. Whereas traditional approaches to programming rely on hardcoded rules, which set out how to solve a problem, step by step
What an AI teaching project would look like?
We suggest setting up a project based around the theme machines of the future, which should take around five hours.
There are several free resources and lesson plan ideas covering this theme on the CREST Awards website.
To begin the project, students should form teams and work in their groups to find out about machine learning and come up with an idea for using their machine in a home environment.
To do this, they will need to:
- Research existing machine learning tools and explore the future potential of this technique
- Develop a concept for their own machine learning tool
- Decide on what data they would need to collect and how they would source the data
- Create a plan for how the machine might process the data and how this would be useful for humans
- Draw a detailed design for the physical form of their machine learning tool
- Develop ideas about how to market their product
In their groups, students can experiment with machine learning using a range of different AI-powered tools.
They should explore how machine learning uses examples, rather than instructions, to make decisions, and how the more examples (or data) we train the machine with and the more varied these examples, the more intelligent it will be.
Learning by doing and through investigation will further help students build confidence and take ownership of their project.
Once they have designed their machines, they should present their ideas to the class. For these, encourage them to think about who will do the explaining during the different elements of their presentation and ask each student to present and discuss what their role in the project was.
This project-based based approach to STEM education provides key curriculum-based science learning, while also nurturing important development skills such as critical thinking, leadership, communication, teamwork and reflection, among others.
And vitally, its hands-on nature makes it naturally more engaging to a wider range of learning styles.
Caitlin Brown is education manager at the British Science Association.