A Bigdata Analytic Approach For Finding Instructor’s Performance Based On Students Outcome

Abstract

In education institutions, analyzing the student dataset is performed using the data mining techniques. Based on the academic marks of the student, predicting the tutor performance will be helpful for the institutions to develop their education system. The existing methodologies are mainly performed using the decision tree algorithm which takes more time. In this paper, predicting the mentor performance using K-means algorithm with the MapReduce programming model in an efficient way. The experimental setup is carried out in Hadoop framework with MapReduce programming model. The result analysis is evaluated for accuracy, precision, recall, specificity by comparing with the existing classification schemes. Our proposed technique improvises the prediction accuracy and reduces the time.