Use of data clustering to enhance student and teacher performance
International Journal of Development Research
Use of data clustering to enhance student and teacher performance
Received 02nd March, 2017; Received in revised form 24th April, 2017; Accepted 17th May, 2017; Published online 16th June, 2017
Copyright©2017, Mayank Thaldi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In past decades, number of people interested in online courses has increased exponentially. Many new websites are deployed every day focusing on online courses. Recent research focuses more on teacher's decision making. There is a huge scope for teachers to improve, provided sophisticated tool. In this paper we differentiate student groups based on their score and comments and then provide suitable suggestions to teachers. We achieve this through Regression and Clustering. We will mainly focuses on K-mean algorithm to achieve our desired result. We remove noisy and inconsistent data and provide teachers with suitable solutions. This will result in better teaching and learning experience for both student and the teacher. We will do Regression and Clustering with the help of Weka.. We will host our server on local server using XAMPP and test our results
