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Kyle T. Turner; George Engelhard Jr. – Journal of Experimental Education, 2024
The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…
Descriptors: Data Analysis, Multivariate Analysis, Individual Characteristics, Behavior
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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
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Huie, Emily Z.; Sathe, Risa Uday; Wadhwa, Anish; Santos, Efrain Vasquez; Gulacar, Ozcan – EURASIA Journal of Mathematics, Science and Technology Education, 2022
Concept maps are powerful tools used to reveal challenges in students' learning. However, their use introduces complexities when a large group of students' conceptualizations need to be examined. In this study, concept maps of 344 general chemistry students were analyzed after grouping them based on achievement in chemistry, math proficiency, and…
Descriptors: Concept Mapping, Chemistry, Mathematics Skills, Gender Differences
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You, Hye Sun; Park, Sunyoung; Delgado, Cesar – Science Education, 2021
The purpose of this study is to examine the characteristics of US schools associated with two measures of scientific literacy (content knowledge and "procedural and epistemic" knowledge) using the 2015 Programme for International Student Assessment (PISA) data. Because outcomes are nested within students, and students within schools, a…
Descriptors: Scientific Literacy, Institutional Characteristics, Student Characteristics, Grades (Scholastic)