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Diego Cortes; Dirk Hastedt; Sabine Meinck – Large-scale Assessments in Education, 2025
This paper informs users of data collected in international large-scale assessments (ILSA), by presenting argumentsunderlining the importance of considering two design features employed in these studies. We examine a commonmisconception stating that the uncertainty arising from the assessment design is negligible compared with that arisingfrom the…
Descriptors: Sampling, Research Design, Educational Assessment, Statistical Inference
Ebru Dogruöz; Hülya Kelecioglu – International Journal of Assessment Tools in Education, 2024
In this research, multistage adaptive tests (MST) were compared according to sample size, panel pattern and module length for top-down and bottom-up test assembly methods. Within the scope of the research, data from PISA 2015 were used and simulation studies were conducted according to the parameters estimated from these data. Analysis results for…
Descriptors: Adaptive Testing, Test Construction, Foreign Countries, Achievement Tests
Leslie Rutkowski; David Rutkowski – Journal of Creative Behavior, 2025
The Programme for International Student Assessment (PISA) introduced creative thinking as an innovative domain in 2022. This paper examines the unique methodological issues in international assessments and the implications of measuring creative thinking within PISA's framework, including stratified sampling, rotated form designs, and a distinct…
Descriptors: Creativity, Creative Thinking, Measurement, Sampling
Özmen, Zeynep Medine; Güven, Bülent – Journal of Pedagogical Research, 2022
The present study aimed to remediate pre-service teachers' misconceptions about sampling distributions and to develop their conceptual understanding through the use of conceptual change texts (CCTs). The participants consisted of 84 pre-service teachers. To determine the pre-service teachers' conceptual understanding of sampling distributions, an…
Descriptors: Preservice Teachers, Mathematics Teachers, Sampling, Statistical Distributions
Umut Atasever; Francis L. Huang; Leslie Rutkowski – Large-scale Assessments in Education, 2025
When analyzing large-scale assessments (LSAs) that use complex sampling designs, it is important to account for probability sampling using weights. However, the use of these weights in multilevel models has been widely debated, particularly regarding their application at different levels of the model. Yet, no consensus has been reached on the best…
Descriptors: Mathematics Tests, International Assessment, Elementary Secondary Education, Foreign Countries
Joo, Sean; Ali, Usama; Robin, Frederic; Shin, Hyo Jeong – Large-scale Assessments in Education, 2022
We investigated the potential impact of differential item functioning (DIF) on group-level mean and standard deviation estimates using empirical and simulated data in the context of large-scale assessment. For the empirical investigation, PISA 2018 cognitive domains (Reading, Mathematics, and Science) data were analyzed using Jackknife sampling to…
Descriptors: Test Items, Item Response Theory, Scores, Student Evaluation
Shelby J. Haberman; Sabine Meinck; Ann-Kristin Koop – Large-scale Assessments in Education, 2024
This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal…
Descriptors: Elementary Secondary Education, Foreign Countries, Achievement Tests, Mathematics Achievement
Mang, Julia; Küchenhoff, Helmut; Meinck, Sabine; Prenzel, Manfred – Large-scale Assessments in Education, 2021
Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…
Descriptors: Sampling, Hierarchical Linear Modeling, Simulation, Scaling
Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
Brunner, Martin; Keller, Lena; Stallasch, Sophie E.; Kretschmann, Julia; Hasl, Andrea; Preckel, Franzis; Lüdtke, Oliver; Hedges, Larry V. – Research Synthesis Methods, 2023
Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…
Descriptors: Meta Analysis, Surveys, Research Design, Educational Research
Heine, Jörg-Henrik; Robitzsch, Alexander – Large-scale Assessments in Education, 2022
Research Question: This paper examines the overarching question of to what extent different analytic choices may influence the inference about country-specific cross-sectional and trend estimates in international large-scale assessments. We take data from the assessment of PISA mathematics proficiency from the four rounds from 2003 to 2012 as a…
Descriptors: Foreign Countries, International Assessment, Achievement Tests, Secondary School Students
Yamaguchi, Kazuhiro – Journal of Educational and Behavioral Statistics, 2023
Understanding whether or not different types of students master various attributes can aid future learning remediation. In this study, two-level diagnostic classification models (DCMs) were developed to represent the probabilistic relationship between external latent classes and attribute mastery patterns. Furthermore, variational Bayesian (VB)…
Descriptors: Bayesian Statistics, Classification, Statistical Inference, Sampling
Jiang, Yu; Zhang, Jiahui; Xin, Tao – Journal of Educational and Behavioral Statistics, 2019
This article is an overview of the National Assessment of Education Quality (NAEQ) of China in reading, mathematics, sciences, arts, physical education, and moral education at Grades 4 and 8. After a review of the background and history of NAEQ, we present the assessment framework with students' holistic development at the core and the design for…
Descriptors: Foreign Countries, Educational Quality, Educational Improvement, National Competency Tests
Martin, Michael O.; Mullis, Ina V. S. – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments of student achievement such as International Association for the Evaluation of Educational Achievement's Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study and Organization for Economic Cooperation and Development's Program for International…
Descriptors: Achievement Tests, International Assessment, Mathematics Tests, Science Achievement
Marchionni, Mariana; Vazquez, Emmanuel – Assessment in Education: Principles, Policy & Practice, 2019
In this paper, we estimate the causal effect of an extra year of schooling on mathematics performance for seven Latin American countries based on PISA 2012. To that end we exploit exogenous variation in students' birthdates around the school entry cut-off date using both sharp and fuzzy Regression Discontinuity designs. We find strong effects of…
Descriptors: Achievement Tests, Foreign Countries, Secondary School Students, International Assessment