Survey on data mining approach for analysis and prediction of student performance
Year: 2018
Type: article
Abstract: The quality of education is measured by the academic performance of students and the results they produce. Since the student academic performance is the made up of the environmental, psychological, socio-economic and other factors, it is challenging to measure the aca- demic performance of students. Such difficulties can be reduced by investigation of various factors that influence the student perfor- mance. Many researchers have been used different approaches to identifying the variables that help to predict students’ performance. This survey paper examines various data mining methodologies that have been used to analyze and predict students’ performance.
Authors: Chala Simon, Ybralem Bugusa
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W2962020562