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Kalender Arikan – Journal of Baltic Science Education, 2025
Learning style (LS), either visual or verbal, has become debatable in the f ield of education vis-à-vis its relation to student success. However, it remains a valuable research theme for improving learning activities in the teaching of highly visual science fields, including biology, physics, and chemistry. Previous studies have primarily focused…
Descriptors: Cognitive Style, Biology, Retention (Psychology), Science Education
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
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
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
Filiz, Enes; Öz, Ersoy – Journal of Baltic Science Education, 2019
Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in…
Descriptors: Foreign Countries, Achievement Tests, Science Tests, International Assessment
Suk, Youmi; Kim, Jee-Seon; Kang, Hyunseung – Journal of Educational and Behavioral Statistics, 2021
There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…
Descriptors: Artificial Intelligence, Statistical Analysis, Statistical Inference, Classification
Esther Doecke – Compare: A Journal of Comparative and International Education, 2025
Families are active agents in school systems and apply different strategies of educational advantage to help their children succeed at school. These strategies are planned and enacted by families with their children in mind, but they are always a response to the broader education system design. This article explores how through their strategies…
Descriptors: Foreign Countries, Cross Cultural Studies, Academic Achievement, Classification
Delafontaine, Jolien; Chen, Changsheng; Park, Jung Yeon; Van den Noortgate, Wim – Large-scale Assessments in Education, 2022
In cognitive diagnosis assessment (CDA), the impact of misspecified item-attribute relations (or "Q-matrix") designed by subject-matter experts has been a great challenge to real-world applications. This study examined parameter estimation of the CDA with the expert-designed Q-matrix and two refined Q-matrices for international…
Descriptors: Q Methodology, Matrices, Cognitive Measurement, Diagnostic Tests
von Davier, Matthias; Tyack, Lillian; Khorramdel, Lale – Educational and Psychological Measurement, 2023
Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…
Descriptors: Scoring, Networks, Artificial Intelligence, Elementary Secondary Education
Quílez, Juan – Studies in Science Education, 2019
This study consists of a categorisation of the vocabulary of chemistry, focusing on the terminological difficulties students face when learning this subject. Therefore, this classification intends to provide chemistry teachers an awareness of the language barriers students must overcome in their understanding of this scientific discipline. Two…
Descriptors: Chemistry, Science Instruction, Verbs, Vocabulary Development
Oluwalana, Olasumbo O. – ProQuest LLC, 2019
A primary purpose of cognitive diagnosis models (CDMs) is to classify examinees based on their attribute patterns. The Q-matrix (Tatsuoka, 1985), a common component of all CDMs, specifies the relationship between the set of required dichotomous attributes and the test items. Since a Q-matrix is often developed by content-knowledge experts and can…
Descriptors: Classification, Validity, Test Items, International Assessment
Anjar Putro Utomo; Erlia Narulita; Kinya Shimizu – Journal of Baltic Science Education, 2018
The aim of this research was to assess the classification of science test items of TIMSS grade 8 based on higher order thinking skills (HOTS) and determine whether those classified-science test items can be an assessment tool in science class. Sixteen sample test items of HOTS were chosen from 37 reasoning items of TIMSS 1999, 2003, and 2011;…
Descriptors: Foreign Countries, Achievement Tests, Elementary Secondary Education, International Assessment
Bofah, Emmanuel Adu-tutu; Hannula, Markku S. – Large-scale Assessments in Education, 2017
In large scale international assessment studies, questionnaires are typical used to query students' home possessions. Composite scores are computed from responses to the home resource questionnaires and are used as a measure of family socioeconomic background in achievement comparison or for statistical control. This paper deals with profiling the…
Descriptors: Foreign Countries, Socioeconomic Status, International Assessment, Scores
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen – Grantee Submission, 2016
Despite the growing popularity of diagnostic classification models (e.g., Rupp, Templin, & Henson, 2010) in educational and psychological measurement, methods for testing their absolute goodness-of-fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full-information test statistics…
Descriptors: Goodness of Fit, Item Response Theory, Classification, Maximum Likelihood Statistics
Wendt, Heike; Kasper, Daniel – Large-scale Assessments in Education, 2016
Background: In 2011 the Progress in International Reading Literacy Study (PIRLS) and the Trends in International Mathematics and Science Study (TIMSS) were conducted at fourth grade in a number of participating countries with a shared representative sample. In this article we investigate whether there are multidimensional proficiency patterns…
Descriptors: Achievement Tests, Elementary Secondary Education, Foreign Countries, International Assessment
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