Anzeige
Erschienen in:
2019 | OriginalPaper | Buchkapitel
Prediction of Student Attrition Using Machine Learning
verfasst von : Sarahi Aguilar-Gonzalez, Leon Palafox
Erschienen in: Advances in Soft Computing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Student attrition is one of the most important problems for any school, being it private or public.
In public education, a high attrition rate reflects poorly in the school, as it is wasting public taxes on students that do not finish their majors. In private education, it means the school revenue decreases considerably. Much work has been done on predicting churn rates in the Telecommunication industry, in this work we use similar techniques to predict churn rates in education.
We explore the data extensively and see the possible correlations between attrition and variables like entrance examination, place where the students are from and grades up to the point of abandonment of the major.