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CONFLICT-MONITORING AND THE INTUITIVE ERROR IN QUANTITATIVE REASONING

100%
Gillard E., Schaeken W., Van Dooren W., Verschaffel L.
Studia Psychologica
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2011
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vol. 53
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issue 4
385 – 401
EN
Dual-process theories and the intuitive rules theory are influential in the domain of cognitive psychology and of the psychology of mathematics education respectively. The authors discuss similarities between these frameworks that have developed largely separately. They examine quantitative reasoning with geometrical concepts, a paradigmatic task in the intuitive rules research tradition, from a typical dual-process perspective. First, in two experiments, they validate that intuitive responses result from processes exhibiting two main heuristic processing characteristics as posited in the dual-process framework: fastness and effortlessness. Moreover, they discuss the reaction time (RT) findings with regard to the currently central debate in the dual-process literature about how heuristic and analytic processes interact. A position concerning this topic is currently lacking in the intuitive rules theory. The authors discuss how our RT findings contribute to the theorizing in the current dual-process literature.
2

USING MULTILEVEL MODELLING IN THE ANALYSIS OF EXPERIMENTAL DATA: CUMULATIVE EFFECTS OF STRUCTURAL PRIMING IN CHILDREN

100%
Smolik F.
Studia Psychologica
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2010
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vol. 52
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issue 3
229-242
EN
Multilevel modelling is a flexible alternative to the traditional factorial ANOVA approach in the analysis of experimental data with repeated measures. This article describes a psycholinguistic experiment and provides a detailed account of the data analysis, demonstrating the use of multilevel models to include a continuous predictor and complex assumptions about error variance. The experiment investigated the effects of structural priming on reaction times in a word monitoring task. Pairs of sentences with identical or different syntactic structures were presented to 4- and 5-year-old children, whose task was to respond to a word presented in the second sentence. Multilevel modelling analysis revealed an interaction between the experimental condition and position of the trial within the experiment: the reaction times in the same-structure condition decreased over the course of the experiment, while they increased in the different-structure condition. The analysis demonstrates how can be used multilevel models to detect change in responses over the course of an experimental session.
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