Decision Rule Induction in a Learning Content Management System

Abstract — A learning content management system (LCMS) is an environment to support web-based learning content development. Primary function of the system is to manage the learning process as well as to generate content customized to meet a unique requirement of each learner. Among the available supporting tools offered by several vendors, we propose to enhance the LCMS functionality to individualize the presented content with the induction ability. Our induction technique is based on rough set theory. The induced rules are intended to be the supportive knowledge for guiding the content flow planning. They can also be used as decision rules to help content developers on managing content delivered to individual learner. Keywords — Decision rules, Knowledge induction, Learning content management system, Rough set. I. I NTRODUCTION HE term learning content management system (LCMS) refers to a suite of software tools designed to facilitate learning developers to create, manage and deliver learning content to distant learners [2]. The main features of an LCMS include content creation, content repository management, content delivery and interface, and learning process management such as course enrollment, assessment and performance tracking. An LCMS is adaptive and scalable in that creates proprietary content to meet the needs of individual learner. The system offers course developers a feature to create and manage learning objects as customized content. Thus, the course development process can be viewed as a compilation of pieces of content retrieved from content repository to fit unique needs of different learners. We, therefore, propose a knowledge induction technique to support course developers in designing flow of content

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