We evaluate the “story grammar” approach to story understanding from three perspectives. We first examine the formal properties of the grammars and find only one to be formally adequate. We next evaluate the grammars empirically by asking whether they generate all simple stories and whether they generate only stories. We find many stories that they do not generate and one major class of nonstory that they do generate. We also evaluate the grammars' potential as comprehension models and find that they (...) would add nothing to semantic models that focus on the story content. Hence we advocate a story content oriented approach to studying story understanding instead of the structural story grammar approach. (shrink)

A productive way to think about imagistic mental models of physical systems is as though they were sources of quasi‐empirical evidence. People depict or imagine events at those points in time when they would experiment with the world if possible. Moreover, just as they would do when observing the world, people induce patterns of behavior from the results depicted in their imaginations. These resulting patterns of behavior can then be cast into symbolic rules to simplify thinking about future problems and (...) to reveal higher order relationships. Using simple gear problems, three experiments explored the occasions of use for, and the inductive transitions between, depictive models and number‐based rules. The first two experiments used the convergent evidence of problem‐solving latencies, hand motions, referential language and error data to document the initial use of a model, the induction of rules from the modeling results, and the fallback to a model when a rule fails. The third experiment explored the intermediate representations that facilitate the induction of rules from depictive models. The strengths and weaknesses of depictive modeling and more analytic systems of reasoning are delineated to motivate the reasons for these transitions. (shrink)

One cannot summarize the intent of this insightful and engaging book better than the author himself: “The thesis... is that CTM [the Computational Theory of Mind] does not provide a solution to the philosophical problems that it is heralded as solving—indeed, it involves some deep confusions about computers, symbols, and meaning—but that this does not undercut the possibility that the computer paradigm may provide an important resource... for the development of a mature science of cognition”.