Automatic Syllabus-Oriented Remixing of Open Educational Resources Using Agent-Based Modeling

Abstract

Rapid development of open educational resources (OER) is often motivated by a new educational paradigm. This paradigm tends to address current challenges such as reusing, goal-oriented remixing, revising, and redistributing OER. This paper proposes a system to automatically remix, which is a step towards automatic course generation. This system uses an agent-based modeling (ABM) approach to profile OER and simulate the process of selecting and linking the appropriate ones. Each resource profile provides us with metadata that shows its domain and is completed using an appropriate ontology before agents’ interactions. ABM enables cooperation between OER to satisfy requirements of the input syllabus. Using the interaction ability, the most compatible agents, which cover the concepts of the input syllabus, can be linked. The efficiency of the proposed method is evaluated through applying the implemented system on two datasets: ARIADNE and SlideShare. In our experimental results on OER related to the domain of e-learning, we report on the system precision and user satisfaction. Our approach is generic; it can be used with any OER repository and any content management system with a free reuse and remix license.