Iterationism is specifically a theory of AI and learning. It looks beyond prompt engineering and points to a way of working in classrooms where students may have a shared task of improving AI-generated material for a specific purpose. We shall have more to say on the details of this but processes and products are iterated. They are iterated by the originators and by others and they can begin in class and be continued online in different modes. Iteration is the social glue in collaborative classroom and online learning supported by technology.
AI is advancing at pace with new tools appearing daily. The development of these technologies follows an iterative process as an acknowledged part of improvement and implementation. Although this is a central feature of technology-development, it is not so central in the way it is applied to learning. This is partly because we are still coming to terms with significant changes arising from conversational and generative tools. We are still trying to make sense of these technologies.
The struggle to make sense of these technologies has produced a number of traditional theories for learning which have then been applied to AI. These include Constructivism and Cognitive Load Theory. Such theories are equally useful with or without technology but Iterationism specifically recognises the qualities of the technology relative to ways of learning. Specifically, it is possible to demonstrate knowledge of a subject by showing your ability to improve it. Iterationism is not therefore about building knowledge in the way described in Constructivism, it is instead a way of exploring an issue, refining it, and achieving an improvement congruent with your understanding. This might be done individually, in small groups, or collectively as a whole class.
Iterationism follows the AI development process but in this theoretical framework, iteration is applied consciously and in different ways to learning, teaching, and research. It does this for individual and social learning. It applies equally for informal and formal education. Likewise, it applies as much for in-person or co-located education as it does for online and highly distributed collaboration. In all these cases, iteration with AI, is done multiple times as required and in order to achieve an individual or shared educational goal and to demonstrate understanding of the topic/subject.