Using multi-attribute utility theory to select an information technology (IT) infrastructure for learning object repositories (LOR)

Abstract

The purpose of this article is to apply the methodology to structure the decision problem and select an appropriate LOR architecture. This reflected in the need to invest and improve the technology for educational organizations. Selecting an appropriate infrastructure for LOR is usually a complex decision, because it has conflicting attributes. In situations of uncertainty, multi-attribute utility theory (MAUT) assists in selecting the best alternative according to criteria established by the decision maker. Results demonstrated that the choice of indexing and distributing LOR (A4) is less sensitive to changes and has greater utility. According to the analysis, A4 is the option most suitable for deploying IT infrastructure in the case of application. Researchers and professional managers can assess the types of ROA architecture and replicate this decision model to find similar results.

Keywords

• Distance Education. Information Technology. Learning Objects Repositories. Multi-attribute Utility Theory (MAUT).