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CLASSIFICATION OF DISTANCE EDUCATION STUDENTS BY USING ARTIFICIAL NEURAL NETWORK APPROACH BASED ON STUDENT CONTENTMENT ABOUT ACADEMIC SERVICES AND STUDENT PERFORMANCE
Journal: Electronic Letters on Science & Engineering (Vol.3, No. 2)Publication Date: 2007-09-03
Authors : Elif Yavuz;
Page : 29-37
Keywords : Neural Network; Distance Education; Student Contentment; Student Performance;
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- CLASSIFICATION OF DISTANCE EDUCATION STUDENTS BY USING ARTIFICIAL NEURAL NETWORK APPROACH BASED ON STUDENT CONTENTMENT ABOUT ACADEMIC SERVICES AND STUDENT PERFORMANCE
- FEATURE SELECTION BASED ON CHI SQUARE IN ARTIFICIAL NEURAL NETWORK TO PREDICT THE ACCURACY OF STUDENT STUDY PERIOD
- EFFECT OF ICT ON STUDENT ACADEMIC ACHIEVEMENT, ACADEMIC MOTIVATION AND STUDENT ENGAGEMENT AMONG 9TH CLASS STUDENTS
- Determining the effective factors in engineering education and predicting the increase of academic years with multi-criteria decision making and data mining approach (Artificial Neural Network)
- STUDENT ACADEMIC PERFORMANCE: DOES A STUDENT-SPECIFIC STARTING LINE MATTER?
Abstract
In this study Adapazarı Vocational College distance education students’ contentment on the courses is surveyed and analyzed together with their performances. Later classification of the students is studied by the artificial neural network method and a network is created. Objective of this study is to increase the success of the distance education students by using aforesaid artificial neural network based on student comments and performances.
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Last modified: 2016-02-07 21:28:19