Project - Kyoto, baby

AI-assisted learning for neural networks.

Core idea: 

https://playground.tensorflow.org/ clone with specific targets.

• Experimental Group (A): Users get AI assistance for the first 10 examples (clipy style), then they have 5 test cases without AI.
• Control Group (B): Users get 10 test examples they need to optimise for, with generic rules of how different parameters affect performance, then 5 test cases
  

We record (everything, but we focus on):

• Performance on the 5 test questions (complexity vs performance) and speed
• Engagement between clicks
• If Michalis approves -> performance on the NN assignment (post-intervention performance)
• Self-assessment survey: AI literacy, Intrinsic motivation