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Hsu, Chia-Ling; Chen, Yi-Hsin; Wu, Yi-Jhen – Practical Assessment, Research & Evaluation, 2023
Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…
Descriptors: Bayesian Statistics, Computation, International Assessment, Achievement Tests
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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
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Terzi, Ragip; Sen, Sedat – SAGE Open, 2019
Large-scale assessments are generally designed for summative purposes to compare achievement among participating countries. However, these nondiagnostic assessments have also been adapted in the context of cognitive diagnostic assessment for diagnostic purposes. Following the large amount of investments in these assessments, it would be…
Descriptors: Achievement Tests, Elementary Secondary Education, Foreign Countries, International Assessment
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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
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Toprak, Emre; Gelbal, Selahattin – International Journal of Assessment Tools in Education, 2020
This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…
Descriptors: Comparative Analysis, Classification, Artificial Intelligence, Networks
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Alexander, Nicola A.; Jang, Sung Tae – Educational Policy, 2020
This article explores the associations between the achievement of economically disadvantaged students and the presence of state policies that include student achievement in teacher evaluations. We looked at student achievement across all 50 states from 2007 through 2013. A simple comparison of states with and without the policy suggested that…
Descriptors: State Policy, Poverty, Academic Achievement, Economically Disadvantaged
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Stocker, Joana; Abu-Hilal, Maher; Hermena, Ehab; AlJassmi, Maryam; Barbato, Mariapaola – Educational Psychology, 2021
This study aims at testing the generalisability of Marsh's Internal/External (I/E) frame of reference model as well as its Dimensional Comparison Theory (DCT) extension in a sample of United Arab Emirates (UAE) high school students. Relationship between self-concept and achievement in Arabic, English and mathematics were explored. A sample of 990…
Descriptors: Arabs, High School Students, Self Concept, Academic Achievement
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
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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
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Güzeller, Cem Oktay; Eser, Mehmet Taha; Aksu, Gökhan – International Journal of Progressive Education, 2016
This study attempts to determine the factors affecting the mathematics achievement of students in Turkey based on data from the Programme for International Student Assessment 2012 and the correct classification ratio of the established model. The study used mathematics achievement as a dependent variable while sex, having a study room, preparation…
Descriptors: Foreign Countries, Mathematics Achievement, Secondary School Students, Grade 10
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Leitão, Ulisses Azevedo – Education Policy Analysis Archives, 2015
In this article, I propose an index, called the Social Index of Educational Effectiveness (SIEE), which allows the establishment of an objective criterion to define the school's profile concerning the promotion of educational equity. It makes it possible to differentiate schools with an "inclusionary profile," (SIEE>0), from those…
Descriptors: Educational Administration, School Effectiveness, Profiles, Equal Education
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Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling – Educational and Psychological Measurement, 2015
When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…
Descriptors: Test Items, Item Response Theory, Research Methodology, Decision Making
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Miller, Daniel C. – School Psychology Forum, 2015
The Woodcock-Johnson-Fourth edition (WJ IV; Schrank, McGrew, & Mather, 2014a) and the Wechsler Intelligence Scale for Children-Fifth edition (WISC-V; Wechsler, 2014) are two of the major tests of cognitive abilities used in school psychology. The complete WJ IV battery includes the Woodcock-Johnson IV Tests of Cognitive Abilities (Schrank,…
Descriptors: Cognitive Ability, Cognitive Tests, Children, Intelligence Tests
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Han, Bing; Dalal, Siddhartha R.; McCaffrey, Daniel F. – Journal of Educational and Behavioral Statistics, 2012
There is widespread interest in using various statistical inference tools as a part of the evaluations for individual teachers and schools. Evaluation systems typically involve classifying hundreds or even thousands of teachers or schools according to their estimated performance. Many current evaluations are largely based on individual estimates…
Descriptors: Statistical Inference, Error of Measurement, Classification, Statistical Analysis
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Slama, Rachel B. – American Educational Research Journal, 2014
Using eight waves of longitudinal data on a statewide kindergarten cohort of English learners (ELs), I examined ELs' tenure in language-learning programs and their academic performance following reclassification as fluent English proficient. I employed discrete-time survival analysis to estimate the average time to and grade of reclassification…
Descriptors: English Language Learners, Cohort Analysis, Longitudinal Studies, English (Second Language)
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