In this chapter, we explored theories of learning and how learning computer science fits into them. In particular, we saw that learning computer science and programming creates new structures in the mind corresponding to physical changes in the connections between brain neurons. Piaget’s genetic epistemology theory tells us the process of building these structures requires a certain amount of cognitive disequilibrium - grappling with the subject material and trying to make sense of it.
Carol Dweck’s theory of mindsets helps us understand how students respond to this disequilibrium. Ideally our students adopt a growth mindset which encourages them to continue to work at learning the material, eventually building those mental structures. Vigotksy’s zone of proximal development helps define how much disequilibrim we need to create, and provides some guidance on how to control that.
Pigaet’s stage theory, as elaborated in the developmental epistemology of programming, gives us a way to reason about where students’ development is. And the neo-Piagitian overlapping waves model helps us understand that development is specific to individual concepts within the domain. And finally, internalized notional machines are a way of understanding exactly what some of those mental structures our students are building are - a mental model of how the computer and programming language work together that helps them design and write programs.