9309667 BATCHELDER This project will continue research on a class of formal cognitive models known as general processing tree (GPT) models. GPT models are a special class of simple statistical models that have great potential to help researchers measure unobservable cognitive capacities, such as memory storage, memory organization, and retrieval capacity. Prior research involved the invention of a number of new models and their application to different issues in human memory, including bilingualism, eyewitness memory, mnemonics, source memory, and memory loss in the elderly. Also, advances in the statistical theory behind this type of modeling have led to the work beginning to have an impact on the basic research of a number of psychologists. The goal of this new project is to expand this research program and take it to the "next level." This will include the development of new GPT models and expansion of their application to a wider range of topics in psychology. For example, one project will take current complex theories of human cognition and represent them approximately with more simple GPT models. Recent research suggests that the class of cognitive models that can be represented in this manner is quite large. When theoretical models are expressed in GPT form, the extensive statistical theory behind GPT modeling can provide a simple yet thorough method for evaluating and understanding the models. Another project will explore the use of GPT models to measure different types of logical-reasoning capacities, such as the ability to find confirming and disconfirming evidence for a hypothesis. The research will develop GPT models to disentangle these and other factors in reasoning. The result should be a clearer idea of how to assess a person's logical strengths and weaknesses. In addition, the research will include further analysis of the statistical and structural properties of GPT models. This analytic work will include extending the models to han dle individual differences in cognitive abilities and also expanding them to analyze the time it takes to make various responses (i.e., reaction-time data). Finally, a major goal of this project is to develop and document user-friendly software programs on the use of GPT models. The material will be targeted to a large class of research psychologists and will include a general overview of GPT modeling, examples from inside and outside psychology, and the statistical results from this research. The computer programs will be general enough to enable researchers to develop, analyze, and test their own GPT models in a wide variety of situations. These materials will serve to make this methodology more accessible to other psychologists. ***
