Saltar al contenido principal

ETHNOS_APP

Inicio • Búsqueda • Revistas • Lista 0

A framework for comparing large-scale survey assessments

Contrasting India’s NAS, United States’ Naep, and OECD’s Pisa

Datos Bibliográficos

ID22168317
AutoresPeter van Rijn, Peter W van Rijn (0000-0002-4865-9723, Amsterdam Institute for Global Health and Development, autor de correspondencia), Han‐Hui Por (Educational Testing Service), Han-Hui Por, Daniel F Mccaffrey (0000-0003-1196-5273, Educational Testing Service), Indrani Bhaduri, Jonas Bertling (Educational Testing Service)
Año2024
Volumen9
Fecha de publicación2024-09-25
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Education (JOURNAL)
Identificadores de la revistaISSN: 2504-284X • E-ISSN: 2504-284X
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/feduc.2024.1422030
OpenAlexW4402825182
IdiomaEN
Referencias citadas26

Large-scale survey assessments (LSAs) are important tools for measuring educational outcomes and shaping policy decisions. We present a framework for comparing LSAs to facilitate studying the impact of design choice on the precision of results, contrasting India’s National Achievement Survey (NAS), the United States’ National Assessment of Educational Progress (NAEP), and the OECD’s Programme for International Student Assessment (PISA). Our framework focuses on four key elements: sampling design, assessment design, analysis methodology, and reporting. The notion of total survey error, which is the accumulation of errors across the four key elements, can be used for both designing and evaluating LSAs. As example, we compare statistics that are commonly (but not always) reported from NAS, NAEP, and PISA to summarize outcomes related to sampling, measurement, and reporting. Our examination reveals several key similarities and differences among the three assessments, thereby highlighting the nuanced ways in which each LSA is tailored to meet the specific needs of their purpose and the challenges they face

Cartography · Geography · Regional science · Agricultural risk and resilience · Income, Poverty, and Inequality · Social and Economic Development in India

  • Test Equating, Scaling, and Linking

    Open Access•Michael J Kolen, Robert L Brennan•Test Equating, Scaling, and Linking•2004

  • Estimating Population Characteristics From Sparse Matrix Samples of Item Responses

    Open Access•Robert J Mislevy, Albert E Beaton et al.•Journal of Educational Measurement•1992

  • The Multidimensional Random Coefficients Multinomial Logit Model

    Open Access•Raymond J Adams, Mark Wilson et al.•Applied Psychological Measurement•1997

  • Randomization-Based Inference about Latent Variables from Complex Samples

    Open Access•Robert J Mislevy•Psychometrika•1991

  • The role of plausible values in large-scale surveys

    Open Access•Margaret Wu•Studies In Educational Evaluation•2005

  • The Total Survey Error Approach

    Herbert F Weisberg•Total Survey Error Approach•2005

  • Multiple Imputation for Nonresponse in Surveys

    Open Access•Donald B Rubin•Multiple Imputation for…•1987

  • The Determination of Sample Size

    Jerome Cornfield•American Journal of Public Health…•1951

  • Total Survey Error

    Paul P Biemer•Public Opinion Quarterly•2010

  • Total Survey Error

    Robert M Groves, Lars Lyberg•Public Opinion Quarterly•2010

Velocidad de citaciónhistorical
Altamente citadoNo
Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae