Advisory System for Student Enrollment in University Based on Variety of Machine Learning Algorithms

The enrollment process of students in the Egyptian universities is mainly based on student final grades in high school. The high school final grade doesn’t reflect promising student to admit in specific faculty such as engineering and science, which requires specific student skills and knowledge. In this paper, we present a predictive model for student to help him select the best suitable faculty based on his grades for different subjects in high school. Moreover, the model takes into consideration the country state, in which the student is located, and the gender of the student. The proposed model acts as an advisory and recommendation system for the student, helping him make a mature decision. The model is applied on selective case study, namely, the student enrollment process in faculty of Engineering, Al-Azhar University in Egypt. The enrollment process in the aforementioned university only accepts students graduated from Al-Azhar high schools, which employs different courses, beside the Islamic and Arabic subjects. The experimental results showed that, the model will effectively help faculty management in identifying the key success features in each student, and thus, can filter applicants based on intelligent predictive criteria. The model was intensively tested, and promising results were obtained