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.
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3 years ago

Machines of the future student pack

  • Text
  • Workshop
  • Improve
  • Films
  • Patterns
  • Netflix
  • Examples
  • Output
  • Flowchart
  • Bees
  • Threes
This resource is published under an Attribution - non-commercial - no derivatives 4.0 International creative commons licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Workshop 2: Machine

Workshop 2: Machine learning now Flow diagram – to be used with case studies 2 and 3 1. 1. Data (input): Place card here What is the content of the data? E.g. pictures of bees and threes from the video you watched at the beginning 5. Place card here Where does the data come from? 2. Place card here 2. Algorithm What does the machine or system do with the data? E.g. ‘Look’ for patterns in all the photos of threes and all the photos of bees 5. Feedback How does the machine use the results to improve its performance? E.g. ‘Remembers’ which answers were correct and incorrect and uses this to improve pattern recognition and identify future pictures more accurately 3. Place card here 3. Output What output does the machine produce? E.g. Sorts each photo into either bee or three 4. Test How does the machine know how well it has done? E.g. Checks if the picture has been correctly sorted by comparing its response to the responses given by a human/humans. 4. Place card here 8

Case study 2: AI duet (to be used with the basic flowchart OR flow diagram) The machine plays a tune back to the user. It looks for patterns in what rhythms and melodies people like and play. It uses this information to compose a tune to play back to the user. The machine rates its own performance based on how long people listen to the tune and how highly they rate it. The user plays a tune. The machine stores informati on about which tunes people like and the tunes they have been playing. The user listens to the tune and gives it a rating to show how much they like it. Case study 3: Factory production (to be used with the basic flowchart OR flow diagram) The machine builds the model using the pieces available. Using the stored information, the machine chooses the quickest method given the blocks available. The machine records how long it took to make the model and the method it used. It compares this to previous attempts. 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. Pictures of blocks. The machine uses a camera to ‘see’ the blocks available. It stores information about different building methods. 9

Discovery

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