Alternative Assessment of Performance of Students Through Data Mining

Abstract

This paper is a summary of extensive analytics implemented over personally collected through educational aspect dataset to get insights for their academic analytics. The main focus is on educational data mining. Basically, students progress is directly associated with their obtained marks. Apart from their studious approach, it is possible to have some other perspective effects on their performance. It is known that individuality, lifestyle and responsiveness related variables have close association together which harshly affect student’s performance. The multivariate analysis of variance statistical technique is used to escalate the same and the analytics were carried out with SPSS software package. The obtained results highlighted that personal his/her habitat details affect on their performance.