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Kaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Large-scale Assessments in Education, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
David Kaplan; Jianshen Chen; Weicong Lyu; Sinan Yavuz – Grantee Submission, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
Elaine Allensworth; Alex Gordon; Christopher Young – Annenberg Institute for School Reform at Brown University, 2025
There is considerable variability in the literacy assessments taken in Kindergarten through second grade, across schools and between multilingual learners and other students, and within students over time. This makes it difficult to study changes in students' acquisition of ELA skills in these formative years, or to evaluate policies and practices…
Descriptors: Literacy, Kindergarten, Grade 1, Grade 2
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Mau, Steffen – International Studies in Sociology of Education, 2020
The process of quantification is a powerful development shaping many domains of life today. In the area of education, for example, performance measurement, testing and ranking have become common tools of governance. Quantification is not a neutral way of describing society, but a process of valorisation. It has three sociologically relevant…
Descriptors: Statistical Analysis, Social Influences, Research Methodology, Evaluation Methods
NWEA, 2018
When Superintendent Curtis Craig, Ed.S., came to the Rensselaer Central Schools Corporation in 2015, he discovered an assessment problem common to many districts. The assessment results--Renaissance STAR and Acuity at the time--were not well aligned to the new, more rigorous standards the district and state had recently adopted. In addition, some…
Descriptors: Alignment (Education), Student Evaluation, Academic Standards, School Districts
Provasnik, Stephen; Dogan, Enis; Erberber, Ebru; Zheng, Xiaying – National Center for Education Statistics, 2020
Large-scale assessment programs, such as the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS), employ item response theory (IRT) and marginal estimation methods to estimate student proficiency in specific subjects such as mathematics, science, or reading. Each of these…
Descriptors: Student Evaluation, Evaluation Methods, Academic Achievement, Item Response Theory
Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
Large-scale assessments (LSAs) use Mislevy's "plausible value" (PV) approach to relate student proficiency to noncognitive variables administered in a background questionnaire. This method requires background variables to be completely observed, a requirement that is seldom fulfilled. In this article, we evaluate and compare the…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Statistical Inference
Piro, Jody S.; Dunlap, Karen; Shutt, Tammy – Cogent Education, 2014
As the quality of educational outputs has been problematized, accountability systems have driven reform based upon summative assessment data. These policies impact the ways that educators use data within schools and subsequently, how teacher education programs may adjust their curricula to teach data-driven decision-making to inform instruction.…
Descriptors: Summative Evaluation, Intervention, Preservice Teachers, Data Collection
Cresswell, John; Schwantner, Ursula; Waters, Charlotte – OECD Publishing, 2015
This report reviews the major international and regional large-scale educational assessments, including international surveys, school-based surveys and household-based surveys. The report compares and contrasts the cognitive and contextual data collection instruments and implementation methods used by the different assessments in order to identify…
Descriptors: International Assessment, Educational Assessment, Data Collection, Comparative Analysis
Kubinger, Klaus D.; Rasch, Dieter; Yanagida, Takuya – Educational Research and Evaluation, 2011
Though calibration of an achievement test within psychological and educational context is very often carried out by the Rasch model, data sampling is hardly designed according to statistical foundations. However, Kubinger, Rasch, and Yanagida (2009) recently suggested an approach for the determination of sample size according to a given Type I and…
Descriptors: Sample Size, Simulation, Testing, Achievement Tests
Lockheed, Marlaine E. – OECD Publishing, 2015
This report provides a systematic review and empirical evidence related to the experiences of middle-income countries and economies participating in the Programme for International Student Assessment (PISA), 2000 to 2015. PISA is a triennial survey that aims to evaluate education systems worldwide by testing the skills and knowledge of 15-year-old…
Descriptors: Socioeconomic Status, Adolescents, Foreign Countries, Developing Nations
Taht, Karin; Must, Olev – Educational Research and Evaluation, 2013
We estimated the invariance of educational achievement (EA) and learning attitudes (LA) measures across nations. A multi-group confirmatory factor analysis was used to estimate the invariance of educational achievement and learning attitudes across 55 nations (Programme for International Student Assessment [PISA] 2006 data, N = 354,203). The…
Descriptors: Academic Achievement, Factor Analysis, Factor Structure, Educational Attitudes
de la Torre, Jimmy – Applied Psychological Measurement, 2008
Recent work has shown that multidimensionally scoring responses from different tests can provide better ability estimates. For educational assessment data, applications of this approach have been limited to binary scores. Of the different variants, the de la Torre and Patz model is considered more general because implementing the scoring procedure…
Descriptors: Markov Processes, Scoring, Data Analysis, Item Response Theory
Boyd, Brian T. – School Science and Mathematics, 2008
Classroom tests from nine eighth-grade mathematics teachers were collected from the 2003-04 and 2005-06 school years. These years represent one school year prior to the eighth-grade Ohio Achievement Test (OAT) in mathematics being implemented and the year after the eighth-grade OAT in mathematics was implemented, respectively. In addition,…
Descriptors: Test Items, Student Evaluation, Knowledge Level, Achievement Tests