Discovery challenges (ages 10-14)


Typically completed by 10-14 year olds, students work collaboratively on a five hour project or challenge in self-managed groups. During the project, they use a CREST Discovery passport to record and reflect on their work. Afterwards, students communicate their findings as a group presentation.

Each pack provides teaching guides, kit lists, example timetables and suggested starter activities to help you run your day. Find out more about CREST Discovery Awards.

There are more CREST approved resources that have been developed by our partners and providers specific to your region.


To browse the packs, click the buttons below or scroll down.
Views
2 months ago

Machines of the future teacher pack

  • Text
  • Activities
  • Timings
  • Feedback
  • Teams
  • Powerpoint
  • Develop
  • Workshops
  • Workshop
  • Crest
  • Examples

Contents 3 Background 3

Contents 3 Background 3 Artificial Intelligence (AI) and machine learning The future of machine learning The Royal Society Overview 4 Materials and printing list 5 Timings – one-day project 6 Timings – five-lesson project 7 Step-by-step delivery guide 8 4 Starter activity 10 Everyday examples of AI 11 Facilitation questions 12 About CREST Discovery 13 8 2

Background Over the last few years we have seen big developments in the field of machine learning – a topic that is no longer just a thing of the future. Many of us now interact with systems using machine learning on a daily basis, such as image and voice recognition on social media and virtual personal assistants. Artificial intelligence and machine learning What is AI? AI 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. What is machine learning? Machine learning is a technology that allows computers to learn directly from examples and experience in the form of data. Traditional approaches to programming rely on hardcoded rules, which set out how to solve a problem, step-by-step. In contrast, machine learning systems are set a task, and given a large amount of data to use as examples of how this task can be achieved or from which to detect patterns. The system then learns how best to achieve the desired output. What is an algorithm? An algorithm is a list of rules which can be followed to solve a problem or make a decision. Check out this really simple explanation from BBC Bitesize https://www.bbc.com/bitesize/articles/z3whpv4 What do we mean by machine? In the context of machine learning a ‘machine’ usually refers to a computer that learns directly from examples and experience in the form of data. What is a robot? In the context of machine learning and AI, a ‘robot’ typically refers to the embodied form of AI; robots are physical agents that act in the real world. These physical manifestations might have sensory inputs and abilities powered by machine learning. The future of machine learning In the future, it is likely we will continue to see advances in the capabilities of machine learning, and this exciting process has the potential to change the way we use data in a range of areas. Tools are already being developed to support healthcare, policing, telecommunications, driving and farming. What will be next? The social and economic opportunities which will follow the increased use of machine learning are significant. The Royal Society The Royal Society is the world's oldest independent scientific academy in continuous existence, dedicated to promoting excellence in science. The Society works to recognise, promote, and support excellence in science and to encourage the development and use of science for the benefit of humanity. The Royal Society’s machine learning policy project is investigating the potential of machine learning over the next 5-10 years and exploring how this technology can be developed in a way that benefits everyone. The Royal Society has launched a report setting out the action needed to maintain the UK’s role in advancing this technology while ensuring careful stewardship of its development. The Royal Society has supported the development of this CREST Discovery resource. 3