Development of conditional reasoning: Mental models and information generation

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Conditional reasoning involves making deductive inferences based on if-then premises. It is a key component of advanced reasoning, and understanding its nature and developmental course is a key problem in cognitive psychology. The proposed program of research is an extension of an on-going program that has combined mental model theory (Johnson-Laird & Byrne, 1999; 2002) with an explicit information processing account of model generation (Markovits & Barrouillet, 2002). A key postulate of this model is that conditional reasoning in children, and in unprepared adults, is heavily dependent on processes involved in information retrieval from long term memory (Janveau-Brennan & Markovits, 1999; Markovits & Quinn, 2001), which can be distinguished from more basic probabilistic reasoning (Markovits, Lortie Forgues, & Brunet, 2010; Markovits & Thompson, 2008). Importantly, this model has recently been extended to abstract reasoning (Markovits, 2007; Markovits & Lortie Forgues, in press) by generalizing the notion of information retrieval to that of information generation. Specifically, we have provided evidence that abstract reasoning is facilitated by the ability to generate information about potential alternatives within a contrary-to-fact context. This notion of alternatives generation provides a more coherent context within which the development of reasoning competencies of varying levels of abstraction can be understood. The proposed program will extend these results in the following ways. The major thrust will focus on understanding the developmental progression in the relation between alternatives generation and reasoning. Children at ages between 6 and 15 will be given age-appropriate reasoning tasks, and alternatives generation tasks, using both an experimental and correlational design. Another set of studies will examine the way that information retrieval is used by more or less competent reasoners by using priming and false recognition tasks.