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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
Zhou, Hao; Ma, Xin – Sociological Methods & Research, 2023
Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe…
Descriptors: Simulation, Hierarchical Linear Modeling, Socioeconomic Status, Institutional Characteristics
Aditi Bhutoria; Nayyaf Aljabri; Saheli Bose – International Journal of Child Care and Education Policy, 2025
This paper examines whether parental engagement in early childhood and preschooling act as substitutes, or whether their joint effect enhances students' learning outcomes. We utilize the TIMSS 2019 dataset and employ a hierarchical linear modeling (HLM) approach to analyze data from 52 countries, ensuring a robust examination of cross-national…
Descriptors: Early Childhood Education, Parenting Skills, Child Rearing, Preschool Children
Lyu, Weicong; Kim, Jee-Seon; Suk, Youmi – Journal of Educational and Behavioral Statistics, 2023
This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…
Descriptors: Hierarchical Linear Modeling, Bayesian Statistics, Causal Models, Statistical Inference
Pongsophon, Pongprapan – Science Education International, 2023
This study examined the factors that determined the science achievement of fourth-grade students on the Trends in International Mathematics and Science Study (TIMSS) 2019 in the USA. The data were retrieved from the TIMSS international database and imported to the R program for manipulation. The EdSurvey package was used to conduct multilevel…
Descriptors: Hierarchical Linear Modeling, Predictor Variables, Science Achievement, Elementary School Students
Van Dusen, Ben; Nissen, Jayson – Physical Review Physics Education Research, 2019
Physics education researchers (PER) often analyze student data with single-level regression models (e.g., linear and logistic regression). However, education datasets can have hierarchical structures, such as students nested within courses, that single-level models fail to account for. The improper use of single-level models to analyze…
Descriptors: Physics, Science Education, Educational Research, Hierarchical Linear Modeling
Xiao, Yang; Han, Jing; Koenig, Kathleen; Xiong, Jianwen; Bao, Lei – Physical Review Physics Education Research, 2018
Assessment instruments composed of two-tier multiple choice (TTMC) items are widely used in science education as an effective method to evaluate students' sophisticated understanding. In practice, however, there are often concerns regarding the common scoring methods of TTMC items, which include pair scoring and individual scoring schemes. The…
Descriptors: Hierarchical Linear Modeling, Item Response Theory, Multiple Choice Tests, Case Studies
Herrmann-Abell, Cari F.; Hardcastle, Joseph; DeBoer, George E. – Grantee Submission, 2018
We compared students' performance on a paper-based test (PBT) and three computer-based tests (CBTs). The three computer-based tests used different test navigation and answer selection features, allowing us to examine how these features affect student performance. The study sample consisted of 9,698 fourth through twelfth grade students from across…
Descriptors: Evaluation Methods, Tests, Computer Assisted Testing, Scores
Lorah, Julie – Large-scale Assessments in Education, 2018
Effect size reporting is crucial for interpretation of applied research results and for conducting meta-analysis. However, clear guidelines for reporting effect size in multilevel models have not been provided. This report suggests and demonstrates appropriate effect size measures including the ICC for random effects and standardized regression…
Descriptors: Effect Size, Hierarchical Linear Modeling, Definitions, Regression (Statistics)
Saal, Petronella Elize; van Ryneveld, Linda; Graham, Marien Alet – International Journal of Instruction, 2019
In his State of the Nation address on 7 February 2019, the president of the Republic of South Africa. Mr. Cyril Ramaphosa, stated that the government would provide digital workbooks and textbooks to every school child in South Africa by 2025. (De Villiers, 2019). This announcement begs the question how effective the incorporation of Information…
Descriptors: Correlation, Information Technology, Mathematics Achievement, Foreign Countries
Aru, Sidika Akyüz; Kale, Mustafa – Journal of Education and Training Studies, 2019
The overall aim of this study is to investigate the effect of school-related factors and early learning experiences on mathematics achievement. In this causal-comparative research, HLM analysis was performed on the data of 6378 students, their parents, and 241 school principals and primary school teachers. As a result of the HLM analysis, at the…
Descriptors: Instructional Effectiveness, Mathematics Instruction, Mathematics Achievement, Achievement Tests
Maerten-Rivera, Jaime; Ahn, Soyeon; Lanier, Kimberly; Diaz, Jennifer; Lee, Okhee – Elementary School Journal, 2016
This study was part of the Promoting Science among English Language Learners (P-SELL) efficacy study, a research and development project that implemented a curricular and professional development intervention to improve science achievement of English Language Learners (ELLs) in urban elementary schools. The study used a cluster randomized control…
Descriptors: Intervention, High Stakes Tests, English Language Learners, Science Education
Wang, Cheng-Lung; Liou, Pey-Yan – International Journal of Science Education, 2017
Taiwanese students are featured as having high academic achievement but low motivational beliefs according to the serial results of the Trends in Mathematics and Science Study (TIMSS). Moreover, given that the role of context has become more important in the development of academic motivation theory, this study aimed to examine the relationship…
Descriptors: Student Motivation, Science Education, Science Achievement, Foreign Countries
Sahin, Melek Gülsah; Öztürk, Nagihan Boztunç – International Electronic Journal of Elementary Education, 2018
In this study, it is aimed to examine the effect of classroom assessment on science and mathematics achievements. For this purpose, hierarchical linear modeling (HLM) is performed using variables of like learning science/maths, engage teaching in science/maths, confidence in science/maths, and home resources for learning variables at the student…
Descriptors: Science Achievement, Grade 4, Foreign Countries, Achievement Tests
Knekta, Eva – Scandinavian Journal of Educational Research, 2017
This study investigated changes in reported test-taking motivation from a low-stakes to a high-stakes test and if there are differences in reported test-taking motivation between school classes. A questionnaire including scales assessing reported effort, expectancies, perceived importance, interest, and test anxiety was administered to a sample of…
Descriptors: Student Motivation, Test Wiseness, Grade 9, Tests