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Hurst, Lucas T. – ProQuest LLC, 2022
Rambo-Hernandez and McCoach's analysis into the longitudinal growth of high-achieving students offered two conclusions about the reading growth of high achieving students: high-achieving students lose less ground in reading during the summer, but they exhibit less growth over the school year. This study will seek to replicate the reading results…
Descriptors: Reading Achievement, Mathematics Achievement, Growth Models, High Achievement
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MacArthur, Kelly Rhea; Santo, Jonathan B. – Journal of Statistics and Data Science Education, 2023
This study explores three understudied facets--quadratic effects, change over time, and gender as a moderator--of the otherwise well-documented relationships between statistics anxiety and academic performance. Using pre- and post- course survey data among a sample of 111 undergraduate students in Social Statistics courses at a U.S. Midwestern…
Descriptors: Hierarchical Linear Modeling, Mathematics Anxiety, Statistics Education, Student Attitudes
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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
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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
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Xu, Jianzhong; Corno, Lyn – Metacognition and Learning, 2022
Informed by two theoretical models of homework effects, we extended a model of homework on mathematics achievement in a large sample of Chinese eighth graders. Our model incorporated six clusters of homework variables -- student background factors, homework characteristics, teacher variables, parent variables, student motivation, and homework…
Descriptors: Models, Homework, Hierarchical Linear Modeling, Foreign Countries
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F. Sehkar Fayda-Kinik; Munevver Cetin – Journal of Computer Assisted Learning, 2025
Background: The unprecedented access to information in the 21st century entails a deep understanding of information and communication technology (ICT)-related factors in education and their impacts on learning and teaching. The role of attitudes towards ICT is a proven factor in student achievement. However, there is no consensus about the…
Descriptors: Information Technology, Technology Uses in Education, Academic Achievement, Secondary Education
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Wang, Faming; Wang, Yehui; Liu, Yaping; Leung, Shing On – Scandinavian Journal of Educational Research, 2023
The importance of the opportunity to learn (OTL) for mathematics achievement has been extensively researched. However, there were still unanswered questions regarding OTL's measurement, analytical level, and relationship with motivational beliefs. To fill in the gaps, we aimed to (1) scrutinize the reliability and validity of OTL, (2) investigate…
Descriptors: International Assessment, Foreign Countries, Achievement Tests, Secondary School Students
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Salloum, Serena J. – American Journal of Education, 2022
Purpose: Collective efficacy (CE)--a group's belief in its capabilities to organize and execute courses of action required to reach a goal--is an important organizational property because it facilitates goal attainment. The purpose of this sequential explanatory mixed-methods study was: (1) to affirm the link between CE and student achievement;…
Descriptors: Self Efficacy, Social Environment, Influences, Academic Achievement
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Courtney, Matthew; Karakus, Mehmet; Ersozlu, Zara; Nurumov, Kaidar – Large-scale Assessments in Education, 2022
This study analyzed the latest four PISA surveys, 2009, 2012, 2015, and 2018, to explore the association between students' ICT-related use and math and science performance. Using ICT Engagement Theory as a theoretical framework and a three-level hierarchical linear modeling approach, while controlling for confounding effects, ICT-related…
Descriptors: Technology Uses in Education, Student Attitudes, Mathematics Achievement, Science Achievement
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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
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Manuel S. González Canché – AERA Open, 2023
Research has shown that mathematical proficiency gaps are related to students' and schools' indicators of poverty, with fewer studies on neighborhood effects on achievement gaps. Although this literature has accounted for students' nesting within schools, so far, methodological constraints have not allowed researchers to formally account for…
Descriptors: Mathematics Achievement, Achievement Gap, Educational Research, Regression (Statistics)
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Forrow, Lauren; Starling, Jennifer; Gill, Brian – Regional Educational Laboratory Mid-Atlantic, 2023
The Every Student Succeeds Act requires states to identify schools with low-performing student subgroups for Targeted Support and Improvement or Additional Targeted Support and Improvement. Random differences between students' true abilities and their test scores, also called measurement error, reduce the statistical reliability of the performance…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
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Regional Educational Laboratory Mid-Atlantic, 2023
This Snapshot highlights key findings from a study that used Bayesian stabilization to improve the reliability (long-term stability) of subgroup proficiency measures that the Pennsylvania Department of Education (PDE) uses to identify schools for Targeted Support and Improvement (TSI) or Additional Targeted Support and Improvement (ATSI). The…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
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Regional Educational Laboratory Mid-Atlantic, 2023
The "Stabilizing Subgroup Proficiency Results to Improve the Identification of Low-Performing Schools" study used Bayesian stabilization to improve the reliability (long-term stability) of subgroup proficiency measures that the Pennsylvania Department of Education (PDE) uses to identify schools for Targeted Support and Improvement (TSI)…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
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Cook, Michael; Ross, Steven M. – Center for Research and Reform in Education, 2022
The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on mathematics achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) mathematics assessment. This study compared mathematics achievement growth of students who used…
Descriptors: Mathematics Achievement, Mathematics Instruction, Program Evaluation, Individualized Instruction