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Testing the multi-component model of human cognitive abilities (TEMCOM)
Date du début: 1 sept. 2012, Date de fin: 31 août 2014 PROJET  TERMINÉ 

"What causes people to differ in their mental abilities? The most replicated result in the study of individual differences is that people who perform better on one kind of mental ability test tend to perform better on other kinds of tests as well. After more than a century of research there is still no scientific consensus on the reasons of this phenomenon.The existence of a general mental ability that permeates any human intellectual activity has been proposed, but this hypothesis does not sit well with findings in cognitive psychology and neuroscience. In his PhD thesis, the Applicant has provided an alternative account, which has been further developed in collaboration with a researcher from Princeton University. This account, the multi-component model of human intelligence (MCM), postulates that all mental tasks tap a vast array of different psychological processes.One of the main reasons behind a century of disagreement on the nature of mental abilities is the separation of what has been called the two disciplines of scientific psychology: experimental and differential. The former is concerned with universal characteristics of human cognition, whereas the latter attempts to explain the causes of variation in mental abilities.The MCM provides a model of individual differences that stems from contemporary advances in experimental cognitive psychology and neuroscience. Yet, in order to yield a theory that overcomes the separation of the two disciplines, it still has to provide a measurement model for differential psychology as well as a mathematical model of test performance based on modern test theory. The primary aim of the project is to develop these models and test them, along with a specific prediction of the theory, on already available large-scale data sets using structural equation modeling and item response theory.Besides this main goal, the proposal includes two side projects that enable the Applicant to master cutting-edge statistical techniques."