A web-based learning support system for rough sets

Abstract

Web-based learning is gaining popularity due to its convenience, ubiquity, personalization, and adaptation features compared with traditional learning environments. The learning subjects of Web-based learning systems are mostly for popular sciences. Little attention has been paid for learning cutting edge subjects and no such systems have been developed for rough sets. This paper presents the design principle, system architectures, and prototype implementation of a Web-based learning support system named Online Rough Sets (ORS). The system is specifically designed for learning rough sets in a student-centered learning environment. Some special features, such as adaptation, are emphasized in the system. The ORS has the ability of adaptation to student preference and performance by modifying the size and order of learning materials delivered to each individual. Additionally, it predicts estimated learning time of each topic, which is helpful for students to schedule their learning paces. A demonstrative example shows ORS can support students to learn rough sets rationally and efficiently.