Predicting Students' Academic Performances Using Machine Learning Algorithms in Educational Data Mining
Yazarlar (3)
Öğr. Gör. Şenay KOCAKOYUN AYDOĞAN İstanbul Gedik Üniversitesi, Türkiye
Dr. Öğr. Üyesi Turgut Pura İstanbul Gedik Üniversitesi, Türkiye
Fatih Bingül Beykoz Üniversitesi, Türkiye
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Özgün Makale
(Diğer hakemli uluslarası dergilerde yayınlanan tam makale)
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| Dergi Adı | Malaysian Online Journal of Educational Technology (MOJET) | ||
| Dergi ISSN | 2289-2990 | ||
| Dergi Tarandığı Indeksler | Journals Indexed in Eric | ||
| Makale Dili | İngilizce | Basım Tarihi | 11-2024 |
| Cilt / Sayı / Sayfa | 12 / 4 / 131–153 | DOI | 10.52380/mojet.2024.12.4.557 |
| Makale Linki | https://mojet.net/index.php/mojet/article/view/557/289 | ||
| UAK Araştırma Alanları |
Büyük Veri
Yapay Zeka
Makine Öğrenmesi
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| Özet |
| In every culture and era, education is considered the most fundamental reality and rule that societies prioritize and deem essential. Throughout the process spanning thousands of years, from the emergence of writing to the present day, education has undergone various forms and formats of change. Education has been a continuous guide for shaping, influencing, sustaining societies, and maintaining its dynamics throughout these historical processes. The continuous evolution and growth of education systems and formats worldwide, with changes affecting the quality of education, have the potential to influence nations and societies in every field, ultimately leading to the emergence of an informed society, achievable only through quality education. In this study, the aim is to determine the factors affecting students' academic performance and predict students' end-of-term academic grades using machine learning algorithms within the scope of Earned Value Management (EVM). Such studies have |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
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| Google Scholar | 8 |