ABSTRACT
Latent Problem Solving Analysis (LPSA) is a theory of knowledge representation in complex problem solving that argues that problem spaces can be represented as multidimensional spaces and expertise is the construction of those spaces from immense amounts of experience. The model was applied using a dataset from a longitudinal experiment on control of thermodynamic systems. When the system is trained with expert-level amounts of experience (3 years), it can predict the end of a trial using the first three quarters with an accuracy of .9. If the system is prepared to mimic a novice (6 months) the prediction accuracy falls to .2. If the system is trained with 3 years of practice in an environment with no constraints, performance is similar to the novice baseline.
