Eğitimde Kullanılan Erken Uyarı Sistemleri Konusunda Yapılmış Çalışmaların İncelenmesi

Abstract

Veri madenciliği ve yapay zekâ teknolojilerinin ilerlemesiyle öğrencilerin öğretim yönetim sistemleri üzerindeki hareketlerine bakarak geleceğe yönelik davranışları tahmin edilebilir hale gelmiştir. Özellikle riskli öğrencilerin önceden tespit edilerek uyarı vermesi mantığına dayanan erken uyarı sistemleri geliştirilerek uzaktan eğitim veren kurumlara bilgi sağlanmaktadır. Çalışmamızın amacı, erken uyarı sistemleri üzerine yapılan çalışmaların yayın özellikleri ve veri madenciliğine dayalı analiz yöntemi özellikleri açısından incelenerek mevcut durumun ortaya çıkarılmasıdır. Bu amaç doğrultusunda Google Akademik veri tabanından elde edilen veriler içerik analizi yöntemi ile incelenmiş ve elde edilen sonuçlar frekans tabloları halinde sunulmuştur. Erken Uyarı Sistemleri üzerine yapılan çalışmalar incelendiğinde, bu başlıktaki çalışmalara 2014 yılından sonra başlandığı ve 2018 yılında konu ile ilgili çalışma sayısının arttığı görülmüştür. Bu çalışmaların çoğunlukla ABD’de yapıldığı, makale ve bildiri türünde olduğu ve nicel yöntemlerin tercih edildiği tespit edilmiştir. Yapılan deneysel çalışmalarda verilerin, öğrenme yönetim sisteminden alınan sistem kayıtlarından toplandığı ve verilerin çeşitli veri madenciliği teknikleri kullanılarak analiz edildiği sonucuna varılmıştır. Erken uyarı sistemleri konusunda uygulanabilirliği kanıtlanmış bir modelin henüz geliştirilememiş olması bu çalışmadan elde edilen en önemli sonuç olarak değerlendirilebilir.

Keywords

• Erken Uyarı Sistemleri
• Öğrenme Yönetim Sistemi
• Öğrenme Analitkleri
• Veri Madenciliği

Review of Studies on Early Warning Systems Used in Education

Abstract

The development of data mining and artificial intelligence technologies has led to the fact that the future behavior of students has become predictable when looking at their actions in learning management systems. In particular, early warning systems based on the logic of identify at-risk students and give warnings to them are developed and provide information to distance education institutions. This study aims to examine studies of early warning systems used in education in terms of publication characteristics and data mining analysis methods, as well as to identify the current situation. For this purpose, the data obtained from the Google Scholar database was examined by the content analysis method and the results were presented in frequency tables. When the studies on Early Warning Systems were examined, it was seen that the studies on this topic started after 2014 and the number of studies related to the subject increased in 2018. It was found that these studies were mainly conducted in the United States, represented by articles and conference reports, and the preference was given to quantitative methods. Pilot studies concluded that data was collected from system records taken from a learning management system and that the data was analyzed using a variety of data mining techniques. It can be said that a model that has proven applicability in early warning systems has not been developed yet and this is one of the important results obtained from this study.

Keywords

• Early Warning Systems
• Learning Management System
• Learning Analytics
• Data Mining

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