Analyzing the school performances in terms of lys successes through using educational data mining techniques: Istanbul sample, 2011 LYS baarilarina göre okul performanslarinin eǧitsel veri madenciliǧi teknikleriyle incelenmesi: 2011 istanbul örneǧi


Egitim ve Bilim, vol.39, no.172, pp.78-94, 2014 (SSCI) identifier

  • Publication Type: Article / Article
  • Volume: 39 Issue: 172
  • Publication Date: 2014
  • Journal Name: Egitim ve Bilim
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.78-94
  • Keywords: Cluster analysis, Decision tree, Educational data mining, LYS (University Placement Exam)
  • Yıldız Technical University Affiliated: Yes


In this study, 42 different types of high schools in Istanbul from which students took University Placement Exam (LYS) are clustered in terms of their performances. It was also aimed to determine the types of tests that are more efficient among these schools. For this purpose, educational data mining techniques such as clustering and decision tree are used. By deploying the non-hierarchical k-means algorithm, schools are separated into 5 different clusters which have different success level for each of Math-Science (MS), Language and Math (LM) and Language-Social Studies (LS) test scores. It is found that Science High Schools, Private Science High Schools, Anatolian High Schools and Anatolian Teacher Schools found to be in the highest achievement level in all of the test scores. Furthermore, constructed decision tree models with CHAID algorithm show that (1) Chemistry for the score type MS, (2) Math for the score type LM and (3) Turkish Language and Literature for the core type LS were the test types which are primarily effective in the division of schools into clusters.