Application of Data Mining on Students' Quality Evaluation

Data mining approach for prediction of academic success in open and distance education

“…Of the 114 articles analysed within the scope of the research, 34.20% of the 114 articles were related to academic performance (GPA, grade level, high school score, attendance, number of courses per semester); 22.80% on demographic variables (gender, nationality, place of birth, age), 17.50% on behavioural characteristics (hands raised, resources visited, school satisfaction, discussion, class participation, answering questions), 8.80% on psychological characteristics (personality, motivation, learning strategies, learning approach, contextual influence), 8.80% family background (mother and father education, family income, parents' position) and 7.90% school environment characteristics (school size, educational environment, lecturer/teacher behaviour in the classroom) were used to predict performance. Sembiring et al (2011) developed models to predict student performance by analyzing student behaviors and achievements with data mining; He and Zhang (2011) introduced a decision support system based on data mining to support the complex decision-making process of universities by tracking students and making a comprehensive performance evaluation their study. Durairaj and Vijitha (2014) aimed to predict student performance from grade point averages and to develop a trust model using data mining techniques that extract the necessary information for current educational management.…”

The Application of Data Mining Techniques in College Students Information System

“…The current situation of higher education represents the development of the country. It's a good way to manage college students with data mining technology instead of traditional mining manipulation [1][2][3][4][5]. At present, the campus almost all use electronic management by campus card system.…”