Several Semantic Web Approaches to Improving the Adaptation Quality of Virtual Learning Environments

The aim of the paper is to investigate and propose Semantic Web approaches to improving the adaptation quality of Virtual Learning Environments (VLEs). These approaches are the method for semantic search for Web 2.0 tools in VLEs, and the method for curriculum mapping and semantic search for Learning Objects (LOs) in VLEs. In the paper, a special attention is paid to improving the adaptation capabilities of VLE, e.g. its suitability for different learning styles such as VARK. Web 2.0 tools ontology based on VARK model learning activities gives the possibility to develop adaptive learning environment with better access to specific learning content managing tools (i.e. Web 2.0 tools). The learner will only need to enter the name of learning activity into the search system field and the machine offers the appropriate tools to perform this activity. The engine facilitates the search process by optimizing workloads, thereby improving learner’s satisfaction and improving the efficiency and effectiveness of the learning process. Presented curriculum mapping approach makes interoperability and LOs semantic search possible by making use of two smaller controlled vocabularies instead of a very large one on competencies which would be more volatile. One could exchange information on competencies in a multi-lingual and multi-cultural environment by: (1) breaking down competencies, and (2) relating these competency components to multilingual controlled vocabularies. The research results have shown that, in order to improve the adaptation quality of VLEs, it is very important to improve semantic search for both LOs and Web 2.0 tools in VLEs.