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|Title||Mining feature-opinion in educational data for course improvement|
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.
|Published in||International Journal of New Computer Architectures and their Applications (IJNCAA)|
|Series||Volume: 1, Number: 4|
|Publisher||The Society of Digital Information and Wireless Communication|
|Item link||Item Link|
|Files in this item|
|El-Halees, Alaa M._18.pdf||1.286Mb|
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Alasmar, Ahmed M I (الجامعة الإسلامية - غزة, 2016)With the rapid increase in the volume of Arabic reviews that use applications such as online review sites, blogs, forums, social networking, and so forth, comes at an increasing demand for Arabic opinion mining techniques. ...