Title :
Rough set based system for effective E-learning
Author :
Rana, Hemant ; Rajiv ; Lal, Manoj
Author_Institution :
Res. Cell, Univ. Coll. of Med. Sci., Delhi, India
Abstract :
To achieve intelligence over the web is underlying research topic and continuous efforts have been made in this direction. The results of these efforts in its practical form of applications have been achieved using modern tools & techniques. Artificial Intelligence (AI) has evolved as one of the promising technology for achieving intelligence over web. To facilitate quality education, the identification & selection of various factors that may influence a students´ academic performance is very important. Knowing these factors is important for parents & teachers working positively on these factors may improve the performance of the student. . In this paper we propose an approach of decision rule induction to induce knowledge that can facilitate the proper decision making process. The approach for rule induction process is based on AI based rough set theory. The proposed system may be seen as a helping hand to creators of contents, educators and teachers of the course.
Keywords :
Internet; computer aided instruction; learning (artificial intelligence); rough set theory; AI; Web; artificial intelligence; decision making process; decision rule induction; e-learning; electronic learning; quality education; rough set based system; student academic performance; Approximation methods; Decision support systems; Educational institutions; Rough sets; AI; DSS; Decision support system; RSES; RSES 2.2; RST based Decision system; Rough Sets; Rule induction;
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-93-80544-10-6
DOI :
10.1109/IndiaCom.2014.6828126