ABSTRACT
Complex Problem Solving (CPS) is a hybrid between field studies and experimental studies. This paper introduces a new, abstract conceptualization of microworlds research based on two innovations: (1) a problem representation, which treats protocols as objects in a feature space and, (2) a similarity metric which is defined in this problem space. Latent Semantic Analysis (LSA) is used to analyze performance in CPS, using actions or states as units instead of words and trials instead of text passages. Basic examples of applications are provided, and advantages and limitations are discussed.
