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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
Atalay Kabasakal, Kübra; Arsan, Nihan; Gök, Bilge; Kelecioglu, Hülya – Educational Sciences: Theory and Practice, 2014
This simulation study compared the performances (Type I error and power) of Mantel-Haenszel (MH), SIBTEST, and item response theory-likelihood ratio (IRT-LR) methods under certain conditions. Manipulated factors were sample size, ability differences between groups, test length, the percentage of differential item functioning (DIF), and underlying…
Descriptors: Comparative Analysis, Item Response Theory, Statistical Analysis, Test Bias
Elaldi, Senel – Journal of Education and Training Studies, 2016
This study aimed to determine the effect of mastery learning model supported with reflective thinking activities on the fifth grade medical students' academic achievement. Mixed methods approach was applied in two samples (n = 64 and n = 6). Quantitative part of the study was based on a pre-test-post-test control group design with an experiment…
Descriptors: Foreign Countries, Mastery Learning, Models, Reflection
Acar, Tulin – Educational Sciences: Theory and Practice, 2011
The purpose of this study is to examine the number of DIF items detected by HGLM at different sample sizes. Eight different sized data files have been composed. The population of the study is 798307 students who had taken the 2006 OKS Examination. 10727 students of 798307 are chosen by random sampling method as the sample of the study. Turkish,…
Descriptors: Test Bias, Sample Size, Regression (Statistics), Models