%0 Journal Article
%T MINING FEATURE-OPINION IN EDUCATIONAL DATA FOR COURSE IMPROVEMENT
%A Alaa El-Halees
%J International Journal of New Computer Architectures and their Applications
%D 2011
%I Society of Digital Information and Wireless Communications
%X In academic institutions, student comments about courses can be considered as a significant informative resource to improve teaching effectiveness. This paper proposes a model that extracts knowledge from students' opinions to improve and to measure the performance of courses. Our task is to use user-generated contents of students to study the performance of a certain course and to compare the performance of some courses with each others. To do that, we propose a model that consists of two main components: Feature extraction to extract features, such as teacher, exams and resources, from the user-generated content for a specific course. And classifier to give a sentiment to each feature. Then we group and visualize the features of the courses graphically. In this way, we can also compare the performance of one or more courses.
%U http://sdiwc.net/digital-library/web-admin/upload-pdf/00000088.pdf