Machine Learning for Good: introducing a new course from Apps for Good

Across the UK, our courses have impacted 100,000+ students. This year we have a brand new machine learning course available, developed in partnership with SAP.  In this article we’ll explore what machine learning is, why it’s important for students, and how you can bring it into your classroom.

Harnessing opportunities with new tech

The world young people are facing is increasingly volatile, uncertain, and complex. All around us, there’s a growing awareness of both the positive and negative consequences of emerging technologies like machine learning.  By gaining hands-on experience and applying machine learning technologies for good, students can gain new skills and be empowered to harness the opportunities of the digital age.

Machine learning is becoming an increasingly important part of life with technology. While there are some great tools that exist to teach machine learning concepts, there is currently a lack of accessible resources to teach the subject in key stage 3. To address this gap and help teachers get ahead, we have created a machine learning course alongside subject experts.

What is machine learning?

For simplicity’s sake, we’ll describe machine learning as a system where – rather than a computer programmer deciding the best way to sort, organise, classify or use information – a computer program develops its own set of instructions based on information that users feed it. Machine learning algorithms are all around us. They’re powering customer service chatbots, making personalised recommendations for us on Netflix, and helping our iPhones to identify the phrase ‘Hey Siri’.

Machine learning is a topic of interest for many at the moment, as people are understandably excited to unleash the potential of this technology. Recent advances have rapidly improved the performance of machine learning algorithms, within just a few years they have become much more capable. Machines can now learn at a mind-blowing pace and can handle growing amounts of data in shortening amounts of time. Concepts like face detection and image recognition may have been around for a while, but information can now be processed very quickly and at enormous volumes. Machine learning is also being applied in innovative areas, like predicting which medication could be used to fight cancer.

Of course, there is a current debate about potential ethical issues with the application of machine learning. For instance, if you’re training a driverless car, is it more important to protect passengers than pedestrians? When making a decision in an emergency, is it more important to save young people or old people?

It is important for students to explore these implications of emerging technologies, as well as be aware of how this technology is impacting on them personally. When students are able to consider ethical questions as they directly apply new technologies to create solutions for real-world problems they care about, they are gaining new skills as well as nuanced perspectives as future creators of tech for good.

By becoming fluent and confident with new technologies like machine learning, students gain important skills as innovators, problem solvers, and creators. They are preparing to tackle the problems of the future, very likely tackling problems we’re not even aware of yet. With machine learning skills in their repertoire, students will be able to solve bigger and bigger problems faster and faster.

Chatbots for good

The ZOE bot is an example of Apps for Good students creating machine learning solutions for problems they care about. ZOE is a Facebook messenger chatbot that helps Polish students revise for physics classes. ZOE was trained with all the physics notes the student creators had collected together. Since winning at our Poland showcase in 2017, the students have continued to refine and promote ZOE.

AfGTeamZoe
Dominik, Adrian and Maksym of Team ZOE, pitching their chatbot idea to a panel of judges the second annual Apps for Good final in Gdynia, Poland.

Closing the digital skills gap

By exploring machine learning, students are also preparing for the newest jobs in the technology market. Nearly every technology company is considering how machine learning can transform business, and these companies are on the lookout for skilled professionals to help them. With the current skills gap, there aren’t enough people to fill these roles. Students exposed to machine learning concepts are gaining a head start when it comes to future employability, gaining the technical skills to help them succeed in this changing professional landscape.

Let’s look briefly, for instance, at SAP, the market leader in enterprise software. We have partnered with SAP for the past five years, and most recently collaborated with them to create a new machine learning course for teachers. As an organisation, SAP often incorporates machine learning solutions into their products. They place a lot of importance on developing future technology talent and closing the digital skills gap.

Machine learning in the classroom

If you’re interested in teaching your students about machine learning, there are a couple of useful resources out there to help you get started in a fun and easy way. Machine Learning for Kids is a tool created by Dale Lane – a machine learning expert from IBM who previously worked on Watson. It provides a fun way for kids to learn about machine learning by making things with it. Students can use it to train different types of models, create games and work on other interactive projects. The tool builds on existing efforts to introduce and teach coding to children by adding these models to Scratch, allowing students to create projects with the models they’ve trained. Machine Learning for Kids has been carefully pulled together with other helpful resources into our free machine learning course.

The Apps for Good Machine Learning Course

Available now for teachers in the UK, we’ve created a free machine learning course. We’ve provided all of the materials for you! You just need to download them, review them, and decide how you’re going to deliver them in your classroom. Here are some questions you may have:

  • Who’s the course for? Like all of our courses, it’s flexible, but this course is perfect for Year 8 and Year 9.
  • How long is it? It will vary from teacher to teacher, but should take about 10-12 teaching hours.
  • What does Apps for Good provide? You get access to of the lesson plans and primers, a scheme of work, a student workbook, and CPD sessions.
  • How else does Apps for Good back me up? In addition to the materials, we provide opportunities to bring tech experts into your classroom, and even attend industry engagement sessions at exciting companies.
  • What will students learn? The course includes sessions exploring common machine learning algorithms like decision trees, regression, and clustering. It uses block programming and Scratch. There is also an optional python programming session where students can apply these algorithms to imported datasets.
  • I don’t have experience with machine learning, can I still teach this course? No previous knowledge of machine learning  is required! We provide everything you’ll need in the lesson materials.
  • Can my students submit their ideas to the Awards? Yes, there will be prizes available for machine learning at the 2019 Apps for Good Awards.

We have developed this course in collaboration with SAP, the market leader in enterprise software. This course is provided free for non-fee paying schools.

Ready to get started?

All you need to do to is head to our website and sign up. After that, you can immediately begin reviewing the materials. Additionally, you can get in touch with Jo at education@appsforgood.org and she will answer any of your questions.

Through learning about machine learning, including the benefits and ethical issues, we can empower students all across the UK to unlock their confidence, skills, and talent, and to see the difference they can make both in their own lives and the communities around them using emerging new technologies for good. If you asked us, when armed with these tools, the future is looking pretty bright in the hands of these young tech-minded change makers.

 

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