Preprint Article Version 1 This version is not peer-reviewed

Cognitive Modeling in Intelligence Research: Advantages and Recommendations for their Application

Version 1 : Received: 21 April 2018 / Approved: 23 April 2018 / Online: 23 April 2018 (11:18:23 CEST)

A peer-reviewed article of this Preprint also exists.

Frischkorn, G.T.; Schubert, A.-L. Cognitive Models in Intelligence Research: Advantages and Recommendations for Their Application. J. Intell. 2018, 6, 34. Frischkorn, G.T.; Schubert, A.-L. Cognitive Models in Intelligence Research: Advantages and Recommendations for Their Application. J. Intell. 2018, 6, 34.

Journal reference: J. Intell. 2018, 6, 34
DOI: 10.3390/jintelligence6030034

Abstract

Mathematical models of cognition measure individual differences in cognitive processes, such as processing speed, working memory capacity, and executive functions, that may underlie general intelligence. As such, cognitive models allow identifying associations between specific cognitive processes and tracking the effect of experimental interventions aimed at the enhancement of intelligence on mediating process parameters. Moreover, cognitive models provide an explicit theoretical formalization of theories regarding specific cognitive process that may help overcoming ambiguities in the interpretation of fuzzy verbal theories. In this paper, we give an overview of the advantages of cognitive modeling in intelligence research and present models in the domains of processing speed, working memory, and selective attention that may be of particular interest for intelligence research. Moreover, we provide guidelines for the application of cognitive models in intelligence research, including data collection, the evaluation of model fit, and statistical analyses.

Subject Areas

intelligence; cognitive modeling; methods; measurement; practical guidelines

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