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Aksu, 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
Christie, S. Thomas; Jarratt, Daniel C.; Olson, Lukas A.; Taijala, Taavi T. – International Educational Data Mining Society, 2019
Schools across the United States suffer from low on-time graduation rates. Targeted interventions help at-risk students meet graduation requirements in a timely manner, but identifying these students takes time and practice, as warning signs are often context-specific and reflected in a combination of attendance, social, and academic signals…
Descriptors: Dropout Prevention, At Risk Students, Artificial Intelligence, Decision Support Systems
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
Hwang, Gwo-Jen; Panjaburee, Patcharin; Triampo, Wannapong; Shih, Bo-Ying – British Journal of Educational Technology, 2013
Diagnosing student learning barriers has been recognized as the most fundamental and important issue for improving the learning achievements of students. In the past decade, several learning diagnosis approaches have been proposed based on the concept-effect relationship (CER) model. However, past studies have shown that the effectiveness of this…
Descriptors: Mathematics, Learning Problems, Models, Concept Mapping
Klein, Joseph; Ronen, Herman – Journal of Educational Computing Research, 2003
In the light of reports of bias, the present study investigated the hypothesis that administrative educational decisions assisted by Decision Support Systems (DSS) are characterized by different pedagogical and organizational orientation than decisions made without computer assistance. One hundred and ten high school teachers were asked to suggest…
Descriptors: Computers, Secondary School Teachers, Self Efficacy, Decision Support Systems