Educational Data Mining (EDM) and Learning Analytics (LA) research have emerged as
interesting areas of research, which are unfolding useful knowledge from educational …

Student's performance prediction is essential to be conducted for a university to prevent
student fail. Number of student drop out is one of parameter that can be used to measure …

Regression analysis is used to find the trends in the data. The analysis helps to find the
relationship between dependent and independent variables in the dataset. It also suggests …

With the birth of new technologies which can harness data associated with education, the
field of Educational Data Mining (EDM) has bloomed. EDM is a research area which uses …

Educational Data Mining (EDM) is a learning science, and an emerging discipline,
concerned with analyzing and studying data from academic databases. Through the …

Students academic performance is the reflection of both academic background and family
support. This performance record is critical for the educational institution because they can …

Educational systems need innovative ways to improve quality of education to achieve the
best results and decrease the failure rate. Educational Data Mining (EDM) has boomed in …

Despite improvement in the standard of education globally, students' failure rates have risen.
Data mining has been implemented in several domains, including education, for extracting …

Educational data mining has been widely used to predict student performance and establish
intervention strategies to improve that performance. Most studies have implemented …

The improvements in educational data mining (EDM) and machine learning motivated the
academic staff to implement educational models to predict the performance of students and …