Prediction of Student Success Using Enrollment Data
نویسندگان
چکیده
Predicting the success of students as a function of different predictors has been a topic that has been investigated over the years. This paper explores the socio-demographic variables like gender, region lived and studied, nationality and high school degree that may influence success of students. We examine to what extent these factors help us to predict students’ academic achievement and will help to identify the vulnerable students and their need for extra tutoring or similar supportive services at an early time. We analyzed the data of the Epoka University students that have been enrolled from 2007 to 2013. The sample includes 1211 undergraduate students where 716 did and were supposed to complete the three-year bachelor studies in the past six semesters. Based on the data mining techniques the most important predictors for student success were the students’ high school GPA and gender. For students with high school grades below average, females were found to have a higher percentage of success than boys. No significant correlation was found between the students’ success and the demographic information.
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Predicting Academic Success from Student Enrolment Data using Decision Tree Technique
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