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Paul A. Jewsbury; Yue Jia; Eugenio J. Gonzalez – Large-scale Assessments in Education, 2024
Large-scale assessments are rich sources of data that can inform a diverse range of research questions related to educational policy and practice. For this reason, datasets from large-scale assessments are available to enable secondary analysts to replicate and extend published reports of assessment results. These datasets include multiple imputed…
Descriptors: Measurement, Data Analysis, Achievement, Statistical Analysis
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Francis L. Huang – Large-scale Assessments in Education, 2024
The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional…
Descriptors: Hierarchical Linear Modeling, Evaluation Methods, Educational Assessment, Data Analysis
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Alexandru Cernat; Joseph Sakshaug; Pablo Christmann; Tobias Gummer – Sociological Methods & Research, 2024
Mixed-mode surveys are popular as they can save costs and maintain (or improve) response rates relative to single-mode surveys. Nevertheless, it is not yet clear how design decisions like survey mode or questionnaire length impact measurement quality. In this study, we compare measurement quality in an experiment of three distinct survey designs…
Descriptors: Surveys, Questionnaires, Item Analysis, Attitude Measures
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Hiromichi Hagihara; Mikako Ishibashi; Yusuke Moriguchi; Yuta Shinya – Developmental Science, 2024
Scale errors are intriguing phenomena in which a child tries to perform an object-specific action on a tiny object. Several viewpoints explaining the developmental mechanisms underlying scale errors exist; however, there is no unified account of how different factors interact and affect scale errors, and the statistical approaches used in the…
Descriptors: Measurement, Error of Measurement, Meta Analysis, Data Analysis
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Jonas Videbaek Jørgensen – Evidence & Policy: A Journal of Research, Debate and Practice, 2024
Background: Understanding knowledge utilisation in policymaking is a core task for the social and political sciences. However, limitations and biases abound in commonplace approaches to measuring such use. Consequently, we have little systematic evidence of the extent to which knowledge sources are used in policy decisions. Aims and objectives:…
Descriptors: Research Utilization, Policy Formation, Measurement, Content Analysis
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Weicong Lyu; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Data harmonization is an emerging approach to strategically combining data from multiple independent studies, enabling addressing new research questions that are not answerable by a single contributing study. A fundamental psychometric challenge for data harmonization is to create commensurate measures for the constructs of interest across…
Descriptors: Data Analysis, Test Items, Psychometrics, Item Response Theory
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Adam Rajcan; Edgar A. Burns – Australian Universities' Review, 2024
As part of a study investigating research productivity of sociology PhD students in Australia, an application to the federal government's Department of Education, Skills and Employment (DESE) aimed to establish a baseline count of completed sociology doctorates by university. It was anticipated that university totals might be different from PhD…
Descriptors: Foreign Countries, Sociology, Doctoral Students, Graduation Rate
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
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Antonia Petropoulou; Konstantinos Lavidas; Stamatis Papadakis – Educational Process: International Journal, 2024
Background/purpose: Awareness of the mathematical skills and knowledge children possess in their early years is widely accepted. This includes various common positive aspects, not only for educators but also for researchers and policymakers. This study presents a systematic review conducted to meticulously identify empirical studies published in…
Descriptors: Preschool Children, Mathematics Skills, Young Children, Mathematical Concepts
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Zachary K. Collier; Joshua Sukumar; Roghayeh Barmaki – Practical Assessment, Research & Evaluation, 2024
This article introduces researchers in the science concerned with developing and studying research methods, measurement, and evaluation (RMME) to the educational data mining (EDM) community. It assumes that the audience is familiar with traditional priorities of statistical analyses, such as accurately estimating model parameters and inferences…
Descriptors: Educational Indicators, School Statistics, Data Analysis, Information Retrieval