A case study is described which documents the generation of a new hypothesis in the form of a visualizable model. It is argued that several of the processes used were neither deduction nor induction by enumeration. Rather, a new explanatory model was invented via a successive refinement process of hypothesis generation, evaluation, and modification, starting from an initial rough analogy. New predictions emerged when the subject "ran" the model. Thus it appears to be possible to investigate the model construction processes of experts through thinking aloud protocols.

presented indicating that spontaneously generated analogies can play a significant role in expert problem solving. Since not all analogies are valid, it is important for the subject to have a way to evaluate their validity. Three methods for evaluating analogical validity are identified using observations from thinking aloud problem solving protocols as well as examples from Newton and Galileo. In particular, this paper focuses on an evaluation strategy called bridging that has been observed in solutions to both science and mathematics problems. In constructing a bridge, the subject finds an intermediate case that is seen as "in between" the analogous case and the problem situation because it shares important features of both. Many of the bridges observed appeared to be novel inventions created by the subject. These empirical studies have led to the construction of a more detailed theory for how analogies can be used effectively in instruction. Some of the strategies observed in experts appear to have high potential for helping science students overcome persistent misconceptions in the classroom.

This paper discusses evidence from thinking aloud case studies indicating that part of the knowledge used by expert problem solvers consists of concrete physical intuitions rather than abstract verbal principles or equations. One purpose of the paper is to provide empirical documentation of behaviors such as spontaneous references to using intuition, depictive hand motions, and dynamic imagery reports. Although the role of imagery in lower level tasks is becoming more accepted, we currently lack sufficient empirical evidence for its use in higher level thinking. In order to account for cases where subjects appear to be "running a simulation" of an event on the basis of a physical intuition, a model is presented in which a somewhat general and permanent perceptual motor schema controls a more specific and temporary image of a situation. This process is termed "imagistic simulation". The imagery can be kinesthetic as well as visual, and dynamic rather than static, suggesting the involvement of the motor system. Although rules for making inferences from networks of causal relations have been studied, we lack models which analyze the nature of mental simulations underlying a single causal relationship. Such physical intuitions and simulations may provide basic building blocks for constructing visualizable models in science.