Project Title: Interactive Educational Tool for Particle Swarm Optimization  
Student: Gurjasdeep Singh 
Course: BSc in Computer Science with Artificial Intelligence  

Abstract: 
Swarm intelligence (SI) is a fascinating branch of AI inspired by the collective intelligence 
of natural crowds, such as a school of fish or a colony of ants. Having multiple solutions 
communicating concurrently in the same domain brings valuable properties, one of which 
is robustness. This property is a powerful one as it means we no longer have to rely on
the quality of the initial solution, particles will be distributed across the search space where 
they can explore and converge to the best-found solutions themselves. SI is an active and
evolving field thus it’s important that it is taught to new learners in an effective manner. 
Despite being an active field, there is a lack of educational software for SI and its 
algorithms. With focus on its most popular algorithm, Particle Swarm Optimization, this 
dissertation will explore different methodologies to implement an interactive educational 
software tool which teaches the core concept of SI, which is the collective behaviour of
decentralised, self-organised systems. Particle Swarm Optimization serves as a great 
entry for someone interested in learning the field of SI as it illustrates this core concept
well. An educational software tool will be designed and implemented, its effectiveness in 
teaching a learner will be investigated using test participants. The participants pre-test 
results showed an average score of 22% and after using the educational tool, the 
participants post-test results increased to 83%. Overall, the average test score increased 
by 61%. This study has shown that this educational tool is effective in teaching and 
learning as shown in the test outcomes. Based on the results, this tool can be applied into 
teaching as a way to improve learning.