… of the educational data mining case study aimed to address these identified … student dropout
(Section 2). Then, we consider the settings of our EDM case study and present the analysis …

… rates, analyzing and improving student academic performance. Student drop out prediction
… results for predicting student attrition from a large dataset of student demographics and …

… Student drop out prediction is an important and challenging task. In this paper, we showed
preliminary results for predicting student attrition from a large, heterogeneous dataset of stu…

… the decision of students to persist or drop out of their studies is … data mining technique for
predicting student dropout, as we … In fact, in our case, 13.6% of students drop out, as we can …

… that are still active at the year 3 because after that year the number of those students dropping
out to university is very small and not significant from statistical and/or practical purposes. …

… students with high probability of dropping out (dropout-prone … used in our study so as to predict
the dropout-prone students. The set … -based’ group and the ‘students’ performance’ group. …

… In this article we formulate the student drop out prediction … of students. To this end, we
employ classification models that categorize these students into two different classes: ’drop out’ or ’…

… help these students, because some students drop out during the … this study suggested that
ACT math was a powerful predictor … of studies have found math to be a significant predictor of …

… students in a significant manner to predict fu ture success or failure. Rather than ranking …
between students who stay in college and those who drop out. The successful students have …

… Despite long-standing theory, student drop out continues to be a large concern … students
are most likely to attrite. Thus, in addition to predicting student attrition, we also sought to predict …