SUPERVISED LEARNING MODELS FOR STUDENT PERFORMANCE

Abstract

Towards automation to do mundane tasks and the expectations for students already equipped with good programming skills is on the rise. In parallel, there have been a rising number of students who find it difficult to attain the skills necessary in order to get the dream IT job they desire. The aim of this project is to bridge the gap between the employer and the future employee of the company by the use of SPAS at college level. Student performance analysis system (SPAS) is an online web application system which enables students to know prior hand if their level of skills for the placement is enough to get placed or not, given the necessary inputs. SPAS have an intelligent learning algorithm which utilizes a rich database, analyses the records of previous students’ traits and develops a model for further prediction. The performance evaluation of students by SPAS is by the cumulative predictor algorithm involving generation of several random forest trees on the available data. SPAS learn and create its model reaching higher accuracy with increasing data availability.