Implications of Dynamic Systems for Future Methodology in Developmental and Learning Science

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Bibliographic Details
Title: Implications of Dynamic Systems for Future Methodology in Developmental and Learning Science
Language: English
Authors: Pascal R. Deboeck, G. John Geldhof, Dian Yu
Source: Review of Research in Education. 2023 47(1):100-115.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 16
Publication Date: 2023
Document Type: Journal Articles
Reports - Descriptive
Descriptors: Research Methodology, Systems Approach, Teaching Methods, Learning Processes, Child Development, Vignettes, Effect Size, Inferences, Educational Theories, Futures (of Society), Self Control, Family Relationship, Stress Variables, Measurement Techniques, Comparative Analysis, Context Effect
DOI: 10.3102/0091732X231218728
ISSN: 0091-732X
1935-1038
Abstract: Children develop and learn within dynamic contexts, yet the simplifying assumptions of common statistical methods often relegate such complexity to unexplained error. This chapter discusses ideas from the dynamic systems literature, which focuses on the interplay within and between components of complex systems, such as individuals and their multitiered contexts. This chapter presents three scenarios highlighting knowledge from the dynamic systems literature. These scenarios have implications requiring reconsidering common approaches to explaining the variance associated with change, the conceptualization of effect sizes, and the use of between-person data and analyses to make within-person inferences. The final section provides resources for moving beyond dynamic metaphors and principles, so theories can be translated into testable hypotheses.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1426936
Database: ERIC
Description
Abstract:Children develop and learn within dynamic contexts, yet the simplifying assumptions of common statistical methods often relegate such complexity to unexplained error. This chapter discusses ideas from the dynamic systems literature, which focuses on the interplay within and between components of complex systems, such as individuals and their multitiered contexts. This chapter presents three scenarios highlighting knowledge from the dynamic systems literature. These scenarios have implications requiring reconsidering common approaches to explaining the variance associated with change, the conceptualization of effect sizes, and the use of between-person data and analyses to make within-person inferences. The final section provides resources for moving beyond dynamic metaphors and principles, so theories can be translated into testable hypotheses.
ISSN:0091-732X
1935-1038
DOI:10.3102/0091732X231218728