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Download full textAksu, Gökhan; Dogan, Nuri – Pegem Journal of Education and Instruction, 2019
The purpose of this study is to compare decision trees obtained by data mining algorithms used in various areas in recent years according to different criteria. In the study, similar and different aspects of the decision trees obtained by different methods for classifying the students as successful and unsuccessful in terms of science literacy…
Descriptors: Data Analysis, Decision Support Systems, Visual Aids, College Students
Aksu, Gokhan; Reyhanlioglu Keceoglu, Cigdem – Eurasian Journal of Educational Research, 2019
Purpose: In this study, Logistic Regression (LR), CHAID (Chi-squared Automatic Interaction Detection) analysis and data mining methods are used to investigate the variables that predict the mathematics success of the students. Research Methods: In this study, a quantitative research design was employed during the data collection and the analysis…
Descriptors: Regression (Statistics), Data Collection, Information Retrieval, Predictor Variables
Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Themes in Science and Technology Education, 2016
Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…
Descriptors: Predictive Measurement, Decision Support Systems, Academic Achievement, Exit Examinations
