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Which tasks measure what? Reflections on executive function development and a commentary on Podjarny, Kamawar, and Andrews (2017)

•Conceptual fuzziness plagues research on executive function in young children.•Updating is often confused with working memory.•Shifting is often confused with a general flexibility.•Tasks are sometimes used in unwarranted ways to measure specific constructs.•A case is made for conceptual and termin...

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Bibliographic Details
Published in:Journal of experimental child psychology 2018-03, Vol.167, p.246-258
Main Authors: Morra, Sergio, Panesi, Sabrina, Traverso, Laura, Usai, M. Carmen
Format: Article
Language:English
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Summary:•Conceptual fuzziness plagues research on executive function in young children.•Updating is often confused with working memory.•Shifting is often confused with a general flexibility.•Tasks are sometimes used in unwarranted ways to measure specific constructs.•A case is made for conceptual and terminological clarity and rigorous modelling. This article provides a selective review of the literature on executive function development and related topics, focusing on the conceptual and terminological confusions that might hinder communication among researchers in the field. The distinctions between working memory and updating, and between shifting and flexibility, are discussed. Methodological problems, which have implications regarding whether a certain task can be considered a measure of a psychological construct, are also discussed. Research on preschoolers is examined with particular attention because it is a rapidly growing but controversial field that seems in particular need of greater conceptual clarity. As a specific touchstone case, we discuss whether the Multidimensional Card Selection Task (MCST) created by Podjarny, Kamawar, and Andrews (2017) should better be considered a measure of concurrent cognitive flexibility or working memory capacity. It is argued that connecting tasks to theoretical constructs is not warranted unless based on rigorous empirical testing of well-formulated models.
ISSN:0022-0965
1096-0457
DOI:10.1016/j.jecp.2017.11.004