# A Study on Dropout Prediction for University Students Using Machine Learning
## 3 Proposed Method
### Data Description
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Grade table (28 columns)** & & \\ \hline SID & Student ID & Number (11 digits) \\ Year & Year enrolled & Number (4 digits) \\ Semester & Semester enrolled & Number (1 or 2) \\ Grade & Average grade & Number (0–4.5) \\ NumCourse & Number of courses & Number \\ NumF & Number of courses receiving an F grade & Number \\ \hline
**AcademicStatus table (8 columns)** & & \\ \hline SID & Student ID & Number (11 digits) \\ Year & Year enrolled & Number (4 digits) \\ Semester & Semester enrolled & Number (1 or 2) \\ \multirow{2}{*}{Status} & Enrollment status: Admission(0), Enrollment(1), Leave-of-absence(2), Transfer(3), Dropout(4), Graduation(5) & Category \\ Desc & Additional information about the Status field (if required) Transfer & String \\ \hline
**Scholarship table (8 columns)** & & \\ \hline SID & Student ID & Number (11 digits) \\ Year & Year enrolled & Number (4 digits) \\ Semester & Semester enrolled & Number (1 or 2) \\ NumCouns & Number of counseling attended & Number \\ \hline
**ExtraCourse table (16 columns)** & & \\ \hline SID & Student ID & Number (11 digits) \\ Year & Year enrolled & Number (4 digits) \\ Semester & Semester enrolled & Number (1 or 2) \\ NumExtra & Number of extracurricular courses enrolled NumVolun & Number of volunteer participations & Number \\ \hline
**BookLoan table (16 columns)** & & \\ \hline SID & Student ID & Number (11 digits) \\ Year & Year enrolled & Number (4 digits) \\ Semester & Semester enrolled & Number (1 or 2) \\ NumBook & Number of books borrowed & Number \\ AvgPeriod & Average rental period & Number \\ \hline
**StudentInfo table (70 columns)** & & \\ \hline SID & Student ID & Number (11 digits) \\ Name & Student name & String \\ Dept & Department or division name & String \\ Major & Major name & String \\ AdmYear & Year of admission & Number (4 digits) \\ AdmType & Type of admission: Admission(0), Transfer(1) & Category \\ Region & Region of a high school graduated & Category \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Tables and attributes stored in the academic information system of Sahmyook University, which can be used for dropout prediction in the proposed method (underlined attributes represent those that make up a primary key). protect privacy of students. In the example, the student with SID 2012 xxx010 successfully graduated after completing 8 semesters, so the table contains 8 records representing grade information for each semester. Note that each student has an additional record indicating the semester in which he or she graduated or dropped out. In the example below, the 9 th record of 2012 xxx010 indicates that the student graduated in the first semester of 2016. The student with SID 2012 xxx011 was only enrolled for one semester and dropped out. Table 4 shows example records of two dropout students in the AcademicStatus table. The student with SID 2012 xxx012 entered as a freshman in the first semester of 2012, took a leave of absence for two semesters in 2013, and finally dropped out in the first semester of 2014. The student with SID 2012 xxx013 entered as a transfer student, attended two semesters, and dropped out in the first semester of 2013. As mentioned before, all tables except StudentInfo contain student records by semester, and they have the same number of records, 168,000. On the other hand, StudentInfo contains records by SID and consists of 20,050 records. The table stores information such as student name, department, major, year of admission, admission type (freshman, transfer, etc. ), and region of the high school from which the student graduated for each student.