Universal Journal of Educational Research · 2017 · 14 citations · 38 references
EducationSecondary EducationEducational Data MiningPerformance AssessmentStudent EngagementAcademic FunctioningDemographic Analysis For EducationStudent Achievement AnalysisStudent Demographics AnalysisStudent SuccessStudent Success AnalyticsAutomatic Interaction DiscoveryChaid AlgorithmDecision-tree AnalysisParental Employment StatusStudent Performance AnalysisStudent Success Prediction
This study aims to determine students' characteristics that predict their academic success. The study group consisted of 4229 students studying at middle schools in Burdur. The data were collected using a questionnaire in the 2014-2015 academic year and analyzed using CHAID (Chi-squared Automatic Interaction Detection) analysis, a type of decision-tree technique. The CHAID analysis was completed with 10 branches and 18 nodes, and indicated that students' academic success (end-year success grade) was explained by certain factors including mothers' and fathers' educational status, going to an educational center, parents' employment status and parents' monthly income. The most important parental characteristic for a student's end-year success grade was found to be the father's educational status.
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Classification and Regression Trees.
Alexander Gordon, Leo Breiman, Jerome H. Friedman et al. · Biometrics · 1984 · 23.9K citations
Classification and Regression Trees.
John Van Ryzin, Leo Breiman, Jerome H. Friedman et al. · Journal of the American Statistical Association · 1986 · 21K citations