Formalising situated learning in computer-aided design

In this paper, we propose and begin to formalise an approach to machine learning in design called situated learning with the purpose of providing a foundation to developing better design tools in an agent-based framework. Situated learning theory postulates that the situations that an expert is exposed to forms the developmental conditions of expertise. We extend and adapt that theory for computer-aided design with the primary objective of learning the use of existing knowledge, rather than simply the knowledge itself. The idea behind situated learning is to learn situations and associate them with some knowledge with the intention of using the knowledge in similar situations.