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Recent data mining innovations in college education include novel techniques for guided selection of courses, predictions of grades, and predictions of success in fulfilling graduation requirements. Attempts have also been made to discover associations among students with sharp learning curves in an effort to address the slow learning impaired ones. This paper suggests a customizable enrollment system based on analysis of multidimensional data storages using the online analytical mining techniques. Such system will empower guardians and enrollment officers with hidden information that can be used in recommending majors of study to students. Unguided selection of majors is among the root causes of two problems students face: dropping out of college and changing majors of studies. The proposed system is expected to reduce both. The system will also help colleges plan enrollments well. |
