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Suparman; Dadang Juandi; Turmudi – Mathematics Teaching Research Journal, 2025
Mathematics achievement of Indonesian students has not been relatively optimal whereby most of the students still have low mathematics achievement. Hence, the present study develops and produces a digital game called Ucing Sumput that is valid, practical, and effective in enhancing the mathematics achievement of Indonesian students. Research and…
Descriptors: Game Based Learning, Mathematics Achievement, Teaching Methods, Probability
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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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Liqun Yin; Ummugul Bezirhan; Matthias von Davier – International Electronic Journal of Elementary Education, 2025
This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…
Descriptors: Multivariate Analysis, Cutting Scores, Achievement Tests, Foreign Countries
Tim Gill – Research Matters, 2025
One of the main aims of Core Maths qualifications when they were introduced into the post-16 curriculum in 2014 was to help students develop their understanding of maths and its application to different subject areas, particularly in relation to further study (e.g., higher education). In this article, we explore whether Core Maths is fulfilling…
Descriptors: Mathematics Education, Classification, Educational Benefits, Dropout Rate
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Carly Oddleifson; Stephen Kilgus; David A. Klingbeil; Alexander D. Latham; Jessica S. Kim; Ishan N. Vengurlekar – Grantee Submission, 2025
The purpose of this study was to conduct a conceptual replication of Pendergast et al.'s (2018) study that examined the diagnostic accuracy of a nomogram procedure, also known as a naive Bayesian approach. The specific naive Bayesian approach combined academic and social-emotional and behavioral (SEB) screening data to predict student performance…
Descriptors: Bayesian Statistics, Accuracy, Social Emotional Learning, Diagnostic Tests