SOFTWARE ARCHITECTURE OF SEMANTIC RECOMMENDATION ENGINE BASED ON DATA ANALYSIS IN LEARNING MANAGEMENT SYSTEMS

The paper presents an approach and software architecture for semantic recommendation of different types of learning resources using learning and gaming analytics of big data produced by modern e-learning platforms and educational games. In order for the system to provide semantic recommendation, the available information for each learner would be used, as well as aggregated statistics on the behaviour of a group of learners. The information will be extracted from the database and through machine learning techniques, the system will analyse and generate personal recommendations. On the other side to achieve, semantic search of resources containing materials related to the search term from the subject area, it will use ontology for the concepts and relationships between them in the subject area in which the educational platform is specialized.