FINDING THE BEST ALGORITHMS AND EFFECTIVE FACTORS IN CLASSIFICATION OF TURKISH SCIENCE STUDENT SUCCESS

TitleFINDING THE BEST ALGORITHMS AND EFFECTIVE FACTORS IN CLASSIFICATION OF TURKISH SCIENCE STUDENT SUCCESS
Publication TypeJournal Article
Year of Publication2019
AuthorsFiliz, E, Öz, E
JournalJournal of Baltic Science Education
Volume18
Issue2
Start Page239-253
PaginationContinuous
Date PublishedApril/2019
Type of ArticleOriginal article
ISSN1648-3898
Other NumbersE-ISSN 2538-7138
Keywordsclassification algorithms, educational data mining, eighth grade, science success, TIMSS 2015
Abstract

Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in educational area was used in this research. EDM methodology was applied to the results of TIMSS 2015 that presents data culled from eighth grade students from Turkey. The main purposes are to find the algorithms that are most appropriate for classifying the successes of students, especially in science subjects, and ascertaining the factors that lead to this success. It was found that logistic regression and support vector machines – poly kernel are the most suitable algorithms. A diverse set of features obtained by feature selection methods are “Computer Tablet Shared”, “Extra Lessons Last 12 Month”, “Extra Lessons How Many Month”, “How Far in Education Do You Expect to Go”, “Home Educational Resources”, and “Student Confident in Science” and these features are the most effective features in science success.

URLhttp://oaji.net/articles/2019/987-1554359678.pdf
DOI10.33225/jbse/19.18.239
Refereed DesignationRefereed
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