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Journals / Electronic Letters on Science and Engineering / 2008 / Cilt: 4 - Sayı: 1

CLASSIFICATION OF DISTANCE EDUCATION STUDENTS BY USING ARTIFICIAL NEURAL NETWORK APPROACH BASED ON STUDENT CONTENTMENT ABOUT ACADEMIC SERVICES AND STUDENT PERFORMANCE

Uzaktan Eğitim Öğrencilerinin Akademik Hizmetlerden Memnuniyetinin Başarı Durumları İle Birlikte Değerlendirilerek Yapay Sinir Ağları İle Sınıflandırılması

Elif Yavuz
Pages
29–37
Publication Date
2008-04-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study Adapazarı Vocational College distance education students’ contentment on the courses is surveyed and analyzed together with their performances.
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Key Findings & Data:Later classification of the students is studied by the artificial neural network method and a network is created.
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Conclusion & Impact: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.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Sinir Ağları · Uzaktan Eğitim · Öğrenci Memnuniyeti

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.

Özet

Bu çalışmada uzaktan eğitim gören Adapazarı Meslek Yüksekokulu öğrencilerinin almış oldukları derslerden memnuniyetleri sorgulanarak ilgili derslerdeki başarı durumları birlikte değerlendirilmiş, uzaktan eğitim öğrencilerinin yapar sinir ağları ile sınıflandırılması problemi ele alınmıştır. Burada amaç, yürürlükte olan dersler ile ilgili öğrenci değerlendirmeleri sonuçlarına göre öğrencilerin başarı durumlarının oluşturulan yapay sinir ağı ile sınıflandırılması ve başarıya etki eden faktörlerin ders bazında incelenerek uzaktan eğitim öğrencilerinin başarılarının artırılmasıdır.

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Cite This Article

Yavuz, E. (2008). CLASSIFICATION OF DISTANCE EDUCATION STUDENTS BY USING ARTIFICIAL NEURAL NETWORK APPROACH BASED ON STUDENT CONTENTMENT ABOUT ACADEMIC SERVICES AND STUDENT PERFORMANCE. Electronic Letters on Science and Engineering, Cilt: 4 - Sayı: 1, 29–37. https://ajindex.com/articles/133689

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