Student academics performance prediction using datamining techniques Available to Purchase

The use of data mining is very common in the educational system. EDM is a new field that can be employed efficiently in the field of education. Several statistical approaches have been employed to examine and predict student performance from various perspectives over the years. Predicting students’ trajectories through the educational process is one of higher education’s toughest concerns today. The EDM employs a number of concepts and theories, including association rule mining, categorization, and clustering. The information gathered can be utilised to better understand the promotion rate, retention rate, transition rate, and success rate of students. The data mining technology is critical in determining how well kids are performing. The classification algorithms can be used to classify and analyse the students’ data set in an accurate manner. The students’ academic performance is influenced by various factors like parents’ education, locality, economic status, attendance, gender and result. The main objective of this work is to use data mining methodologies to study and analyse the students’ performance. The dataset contains information about different students from one college course in a semester.