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.
Machine learning now answers Case study 3 – Factory production 1. Data (input): Pictures of blocks. The machine uses a camera to ‘see’ the blocks available. It stores information about different building methods. 2. Machine learning algorithm (process) Using the stored information, the machine chooses the quickest method given the blocks available. 3. Hypothesis (output): The machine builds the model using the pieces available. 4. Performance (test): The machine records how long it took to make the model and the method it used. It compares this to previous attempts. 5. Feedback: The more models it makes, the more information it stores. It uses this information to make better choices about the method and blocks to use next time.
Challenge Split into teams Project Manager Makes sure the whole team and the project is on track Research Lead Responsible for thinking about where and how to source the voluminous sets of data you will need. Research support for other team members. Software Lead The creative minds behind your program - responsible for the creating the steps needed for your machine to learn and improve, like the ones from the ‘machine learning now’ workshop. Design Lead Responsible for the physical design of the product. Risk Lead Responsible for thinking about the risk vs. utility of your product and how to manage that. How will you help people trust your product? You need to identify the risks involved and ensure that your machine learning tool will be safe and unbiased. Marketing Lead Responsible for developing a marketing plan and thinking about who this tool would be useful for, how and why.