The national educational panel study (NEPS) and methodological innovations in longitudinal large-scale assessments

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.

Authors

Institutions

Publication Details

Journal
Large-scale Assessments in Education
Published
2024-09-26
DOI
https://doi.org/10.1186/s40536-024-00221-y
Citations
1
Primary Topic
Evaluation and Performance Assessment
Type
article
Field-Weighted Citation Impact
0.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The national educational panel study (NEPS) and methodological innovations in longitudinal large-scale assessments

Marie‐Ann Sengewald, Timo Gnambs, Claus H. Carstensen, Tanja Kutscher et al.
1 citations
Large-scale Assessments in Education
Evaluation and Performance Assessment
0.49
article

The national educational panel study (NEPS) and methodological innovations in longitudinal large-scale assessments

Marie‐Ann Sengewald, Timo Gnambs, Claus H. Carstensen, Tanja Kutscher, Christian Aßmann
article en
1 citations

Abstract

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.

Large-scale Assessments in EducationVol. 12(1)
Leibniz Institute for Educational Trajectories (DE), University of Bamberg (DE)
Leibniz-Institut für Bildungsverläufe, Leibniz-Gemeinschaft
Openalex Percentile: Top 31%
Evaluation and Performance Assessment
0.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.