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The monitoring and support of university freshmen is considered very important at many educational institutions. In this paper we describe the results of the educational data mining case study aimed at predicting the Electrical Engineering (EE) students drop out after the first semester of their studies or even before they enter the study program as well as(More)
1 In the emerging field of educational data mining, a strong bias towards data-rich digital learning environments is the current state of affairs [2, table 2]. However, in many educational institutes a lot of regular course data will probably be more readily available. This data may also be used to support and advise students in various ways, for the better(More)
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