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Download full textHikmet Sevgin – International Journal of Assessment Tools in Education, 2023
This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABIDE application in education. The main factor in choosing them for analyses is that they are Ensemble methods…
Descriptors: Algorithms, Mathematics Education, Classification, Mathematics Achievement
Buyukatak, Emrah; Anil, Duygu – International Journal of Assessment Tools in Education, 2022
The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…
Descriptors: Classification, Accuracy, Reading Tests, Achievement Tests
Aksu, Gökhan; Güzeller, Cem Oktay; Eser, Mehmet Taha – International Journal of Assessment Tools in Education, 2019
In this study, it was aimed to compare different normalization methods employed in model developing process via artificial neural networks with different sample sizes. As part of comparison of normalization methods, input variables were set as: work discipline, environmental awareness, instrumental motivation, science self-efficacy, and weekly…
Descriptors: Sample Size, Artificial Intelligence, Classification, Statistical Analysis
Karadavut, Tugba; Cohen, Allan S.; Kim, Seock-Ho – International Journal of Assessment Tools in Education, 2019
Covariates have been used in mixture IRT models to help explain why examinees are classed into different latent classes. Previous research has considered manifest variables as covariates in a mixture Rasch analysis for prediction of group membership. Latent covariates, however, are more likely to have higher correlations with the latent class…
Descriptors: Item Response Theory, Classification, Correlation, International Assessment
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
Bulut, Okan; Yavuz, Hatice Cigdem – International Journal of Assessment Tools in Education, 2019
Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…
Descriptors: Data Analysis, Educational Research, Educational Researchers, Computer Software
