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Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This

Birney, Damian P.; Beckmann, Jens F.

Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This Thumbnail


Authors

Damian P. Birney



Abstract

Despite substantial evidence for the link between an individual’s intelligence and successful life outcomes, questions about what defines intelligence have remained the focus of heated dispute. The most common approach to understanding intelligence has been to investigate what performance on tests of intellect is and is not associated with. This psychometric approach, based on correlations and factor analysis is deficient. In this review, we aim to substantiate why classic psychometrics which focus on between-person accounts will necessarily provide a limited account of intelligence until theoretical considerations of within-person accounts are incorporated. First, we consider the impact of entrenched psychometric presumptions that support the status quo and impede alternative views. Second, we review the importance of process-theories, which are critical for any serious attempt to build a within-person account of intelligence. Third, features of dynamic tasks are reviewed, and we outline how static tasks can be modified to target within-person processes. Finally, we explain how multilevel models are conceptually and psychometrically well-suited to building and testing within-individual notions of intelligence, which at its core, we argue is cognitive flexibility. We conclude by describing an application of these ideas in the context of microworlds as a case study.

Citation

Birney, D. P., & Beckmann, J. F. (2022). Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This. Journal of Intelligence, 10(3), https://doi.org/10.3390/jintelligence10030049

Journal Article Type Article
Acceptance Date Dec 26, 2022
Online Publication Date Aug 1, 2022
Publication Date 2022
Deposit Date Dec 12, 2022
Publicly Available Date Dec 12, 2022
Journal Journal of Intelligence
Electronic ISSN 2079-3200
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 10
Issue 3
DOI https://doi.org/10.3390/jintelligence10030049
Public URL https://durham-repository.worktribe.com/output/1185190

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Published Journal Article (2.1 Mb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/
4.0/).





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