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      Developmental Histories Facilitating the Emergence of Creative Scientific Expertise: The Role of Developed Cognitive Talents, Education, and Social and Cultural Contexts

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          Abstract

          Understanding how individual and contextual factors collectively contribute to the developmental histories that facilitate the emergence of creative expertise in science is improved by considering the contribution of the broad structure of developed cognitive abilities to creativity, prospective research on the high achieving or gifted students who may choose careers in and end up as creative scientists later in life, as well as retrospective studies of established creative scientists themselves and what their educational histories reveal. We first review and elaborate on these connections as documented in research which explore the development of talent, including cognitive mechanisms that include math and spatial reasoning and science related educational opportunities. We propose a research thought experiment that utilizes the multi-trait, multi-method matrix, and bifactor modeling to help understand the true overlap between measurement structures of cognitive and creative aptitudes. Then we explore the social and cultural contexts that may facilitate and/or hinder creative solutions in science through the lens of how these ecosystems influence talent development for gifted students and also the production of elite scientists. Based on this review, some policies will be suggested that may enhance the development of scientific creativity and broader societal innovation and expand the pipeline to include and fully develop the talents of disadvantaged students and provide nurturing environments to improve the likelihood of the emergence of scientific creative expertise.

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          Convergent and discriminant validation by the multitrait-multimethod matrix.

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            Effect size guidelines for individual differences researchers

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              Invited Paper: The Rediscovery of Bifactor Measurement Models.

              Bifactor latent structures were introduced over 70 years ago, but only recently has bifactor modeling been rediscovered as an effective approach to modeling construct-relevant multidimensionality in a set of ordered categorical item responses. I begin by describing the Schmid-Leiman bifactor procedure (Schmid & Leiman, 1957), and highlight its relations with correlated-factors and second-order exploratory factor models. After describing limitations of the Schmid-Leiman, two newer methods of exploratory bifactor modeling are considered, namely, analytic bifactor (Jennrich & Bentler, 2011) and target bifactor rotations (Reise, Moore, & Maydeu-Olivares, 2011). In section two, I discuss limited and full-information estimation approaches to confirmatory bifactor models that have emerged from the item response theory and factor analysis traditions, respectively. Comparison of the confirmatory bifactor model to alternative nested confirmatory models and establishing parameter invariance for the general factor also are discussed. In the final section, important applications of bifactor models are reviewed. These applications demonstrate that bifactor modeling potentially provides a solid foundation for conceptualizing psychological constructs, constructing measures, and evaluating a measure's psychometric properties. However, some applications of the bifactor model may be limited due to its restrictive assumptions.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                03 September 2021
                2021
                : 12
                : 716529
                Affiliations
                [1] 1Department of Education Reform and Department of Psychology, University of Arkansas , Fayetteville, AR, United States
                [2] 2Autism and Developmental Medicine Institute, Geisinger Health System , Lewisburg, PA, United States
                Author notes

                Edited by: Gregory John Feist, San Jose State University, United States

                Reviewed by: Todd Lubart, Université de Paris, France; Aaron Kozbelt, Brooklyn College and the Graduate Center of the City University of New York, United States

                *Correspondence: Jonathan Wai jwai@ 123456uark.edu

                This article was submitted to Developmental Psychology, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2021.716529
                8446382
                34539517
                161ed898-030f-4903-8c82-4afcbbf1aa9c
                Copyright © 2021 Wai and Brown.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 May 2021
                : 11 August 2021
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 125, Pages: 13, Words: 11486
                Categories
                Psychology
                Conceptual Analysis

                Clinical Psychology & Psychiatry
                creativity,aptitudes and abilities,talent development,measurement,scientific expertise

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