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The national educational panel study (NEPS) and methodological innovations in longitudinal large-scale assessments
Kutscher, Tanja; Sengewald, Marie-Ann; Gnambs, Timo; u. a. (2024): The national educational panel study (NEPS) and methodological innovations in longitudinal large-scale assessments, in: Large-scale assessments in education, Berlin ; Heidelberg [u.a.]: SpringerOpen, Jg. 12, Nr. 31, S. 1–11, doi: 10.1186/s40536-024-00221-y.
Title of the Journal:
Large-scale assessments in education
ISSN:
2196-0739
Publisher Information:
Year of publication:
2024
Volume:
12
Issue:
31
Pages:
Language:
English
Abstract:
This editorial introduces a special issue of Large-Scale Assessments in Education (LSAE) that addresses key challenges in analyzing longitudinal data from large-scale studies. These challenges include ensuring fair measurement across time, developing common metrics, and correcting for measurement errors. The special issue highlights recent methodological innovations, particularly for studies like the National Education Panel Study (NEPS), providing approaches for improving the accuracy and robustness of longitudinal educational research. The papers in this issue present advances in methods for estimating trends, incorporating background information, and analyzing longitudinal relationships between constructs. Innovative approaches such as Bayesian modeling for borrowing historical information, continuous-time models for capturing developmental trends, and plausible value estimation provide practical solutions for researchers working with complex longitudinal data. In addition, the issue presents new software tools that facilitate the implementation of these advanced methodologies. Together, these papers contribute to both the theory and practice of educational assessment and provide valuable insights for those working with longitudinal data in national and international panel studies.
Keywords: ; ; ; ; ;
longitudinal large-scale assessment
National Educational Panel Study
Bayesian historical borrowing
plausible value estimation
continuous-time models
educational trend analysis
Type:
Article
Activation date:
April 7, 2026
Versioning
Question on publication
Permalink
https://fis.uni-bamberg.de/handle/uniba/114571