1. Sodarace: Exploring Evolution with Computational Thinking
Paul Curzon
Queen Mary University of London
With support from,
Department for Education,
Google and the Mayor of London
@cs4fn

2. Aims Give you deeper understanding of core topics
Computational Thinking
Computational Modeling
Computational thinking and biology (eg evolution)
Give you practical ways to teach computing and biology in a fun, thought provoking way
Linked activity sheets and booklets can be downloaded from our website:

3. Algorithmic Thinking and Biology
Why does algorithmic thinking matter to a biologist?
We can build computational models (algorithms) to explore their theories
Help them better understand
Computational models also give a powerful way to learn through exploration
For example, we can explore the theory of evolution by creating a model of the way it works

4. Evolution works how?
Individual animals in a population are all slightly different
The differences are coded in their DNA
Some have differences that help them survive
Eg run faster so: escape predators or catch food better
They are more likely to have children
Children are created by sticking together half of each parent’s DNA (with random changes)
Children whose DNA codes those differences that helped their parents survive are also more likely to survive and pass the differences on…

5. Survival of the fittest
One of these creatures was designed
The other evolved from it
over many generations
The fitness test was speed
Notice how all it’s power is in its back legs
Like a cheetah or more extremely a kangeroo

6. Download the Sodarace Kiosk from: sodarace.net
Play with Evolution
Download the Sodarace Kiosk from: sodarace.net

7. Genetic Algorithms
Use evolution to generate algorithmic solutions of problems
Model the space of solutions
represented by ‘digital DNA’
Use mutation and crossover to produce new solutions
Compare them against a fitness test
Only the best solutions survive
Do this for many generations
better and better solutions emerge
Researchers are even exploring this to make computers creative
Evolving art
Evolving music …

8. Computational Thinking
Algorithmic thinking
Turn theories into algorithms that simulate the real world things we are trying to understand
Biology gives us new ways to create algorithmic solutions
Abstraction
Didn’t model every detail of the real world just the laws of interest
Evaluation
We use the algorithms to evaluate our understanding of the real world

9. Twitter: @TeachingLDNComp
More support
On our website to support this session:
Activity sheets
Story sheets
Slides
Details of more worskshops/courses
free unplugged sessions
subsidised courses (e.g. GCSE programming)

10. Together we are Teaching London Computing
Thank you!