Review of Studies on Early Warning Systems Used in Education

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.