EMT: Ensemble Meta-Based Tree Model for Predicting Student Performance

Table 1

Summary of the common attributes used in predicting student performance.

Factors or features	Description	References
(CGPA)	Cumulative grade point average	[11, 13–17]
Internal assessment	Students’ behavior in the class such as exams marks, lab tests, class tests, attendance, and discussions	[5, 11, 12, 13, 18]
Students’ demographic	Students’ characteristics that include gender, age, salary income, and family background	[14, 19–22]
External assessments	Factors coming from student’s environment: student’s behavior out of the class such as extracurricular activities, high school background, social interaction network, and psychometric	[13, 17, 23–26]
Extracurricular activities	Activities which are not essential for normal class activities	[11, 13, 17, 27]
High school background	Preadmission courses for universities	[20–22]
Social interaction network	Interacting among students or instructors by using social networks	[12, 20, 24, 28]
Psychometric	These attributes can be collected after enrolment such as attitude, motivation, personality, and learning strategies	[27, 29, 30]