Learning Content Repositories and Learning Management Systems Based on Customization and Metadata

The main research object of the paper is the analysis of learning content and software customization problems. Learning content is usually described by metadata and stored in Learning Object/Content Repositories (LORs) or Learning (Content) Management Systems (LMSs). Therefore the paper aims at the analysis of the learning content/objects (LOs) metadata as well as LORs and LMSs features/evaluation criteria dealing with learning customization possibilities. The LORs and LMSs quality evaluation criteria are further investigated as the possible optimization parameters, and one of the multiple criteria evaluation and optimization methods is explored to be applied to optimize LORs and LMSs according to the particular learners needs.