The architecture of LCMS and special software tool for creating the smart learning content in form of personal learning collections were designed and implemented within framework of proposed ontology-based approach in the domain of programming languages. The ontological model for knowledge representation was developed including ontologies of learning course domain, learning resource, learner’s profile and personal learning collection. The last one includes the set of semantic rules for creating the personal learning collection. The new two-stage method for electronic learning resources retrieval and integration into personal learning collection was developed based on ontology reasoning rules.
Further evolution of the project implies:
reimplementation of the collection builder as a web application using the Stardog Enterprise Graph Database as a data store and reasoning engine. Stardog is a fast SPARQL query answering, lightweight, transactional, with world class OWL 2 and SWRL reasoning support graph database and using it can improve the speed and scalability of the collection builder;
implementation the software tool as a web application for creating the learning course ontologies;
developing software tool as a web application for annotating the learning resources;
developing ontologies for other university courses;
the learning resources repository (with Stardog backend as a data store) should be further scaled for subject domain of software engineering to provide the creation of personal collections for variety of learning courses.