Kasparov, Vygotsky, and ChatGPT: What a Chess Prodigy and Child Psychologist Can Teach Us about AI in Education

Vygotsky’s model of the Zone of Proximal Development postulates that there are three kinds of tasks that our environment demands from us as we venture through the world: (1) first, there are tasks that we can accomplish individually, (2) secondly, there are tasks that we cannot accomplish alone; and (3) third, we have tasks that we can only accomplish through interaction with a parent, a peer, or a teacher, who guides us through it. According to Vygotsky, task environments (1) and (2) do not provide learning opportunities. They just simply represent tasks we either can do or cannot do. Learning only happens in the third scenario. In this constellation, an individual finds themself in an environment in which they encounter a task that is too difficult to accomplish alone. It is not completely impossible to accomplish the task, but the tasks need to be tackled by the individual collaboratively through interaction with a parent, a teacher, or a peer. In this environment, which is the Zone of Proximal Development, the individual receives guidance and grows through interaction with an expert. This interaction is what Vygotsky calls scaffolding. Vygotsky famously stated, “What a child can do in cooperation today, he can do alone tomorrow” (Vygotsky, 1962: 104). 

Can generative AI offer scaffolding and engage a learner in the Zone of Proximal Development? Yes, we believe generative AI can do that! And not only do we believe that this is possible in carefully designed learning environments, but we go further and argue that the creation of a scaffolding relationship in the Zone of Proximal Development should be the principal objective in any situation where students are asked to use technology in language education. If this goal is not on our mind as teachers, we miss an opportunity and risk using new technologies in novelty-driven ways, merely for the sake of using them.