ABSTRACT

Educational Data mining is a recent trends where data mining methods are experimented for the improvement of student performance in academics. The work describes the mining of higher education students’ related attributes such as behavior, attitude and relationship. The data were collected from a higher education institution in terms of the mentioned attributes. The proposed work explored Behavior Attitude Relationship Clustering (BARC) Algorithm, which showed the improvement in students’ performance in terms of predicting good behavior, average attitude and good relationship with faculty members and Tutors. The Hierarchical clusters were grouped with related similarities and analysis was experimented using WEKA tool. The resulted analysis describes the input parameters were found optimal.