Students' performance analysis system using cumulative predictor algorithm. (15th May 2019)

• Record Type: Journal Article
• Authors: Rose, J. Dafni; Vijayakumar, K.; Sakthivel, S.
• Is Part Of: International journal of reasoning-based intelligent systems. Volume 11:Number 2(2019)
• Page Start: 122
• Page End: 133
• Publication Date: 2019-05-15
• Subjects: educational data mining -- EDM -- decision tree (J48) -- Naïve Bayes' classifier -- JRip algorithm -- bagging method -- standard deviation -- infogain -- entropy gain -- cumulative predictor -- student's performance analysis; Artificial intelligence -- Periodicals; Reasoning -- Periodicals; 006.3
• Languages: English
• ISSNs: 1755-0556

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 has 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 has an intelligent learning algorithm which utilises 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 learns and creates its model reaching higher accuracy with increasing data availability.