Predicting students' performance is one of the most important issues in educational data
mining (EDM), which has received more and more attention. By predicting students' …

When data mining techniques are used in the context of education, they can uncover hidden
knowledge and patterns that can aid in decision-making processes aimed at improving the …

Prediction models that underlie “early warning systems” need improvement. Some predict
outcomes using entrenched, unchangeable characteristics (eg, socioeconomic status) and …

Algorithms and programming are some of the most challenging topics faced by students
during undergraduate programs. Dropout and failure rates in courses involving such topics …

The academic institutions always looking for tools that improve their performance and
enhance individuals outcomes. Due to the huge ability of data mining to explore hidden …

Accreditation is one of the quality measurements for a University. Some elements of these
measurements are students and graduate students. Prevention of students to drop out is a …

Dropout rate in Bangladeshi universities getting high day by day. Especially in engineering
subjects. Massive number of students taking various engineering subjects for their under …

Educational Data Mining (EDM) is used to ameliorate the teaching and learning process by
analyzing and classifying data that can be applied to predict the students' academic …

In undergraduate engineering education, particularly in the area of control systems, it is vital
for students to gain knowledge on the identification of linear systems. Undergraduate …

Blended learning is increasingly used in college teaching, and formative evaluation has
become the main method for assessing student performance. Based on the formative …