Extended metadata model for digital learning resources

The key aim of using information technology (IT) in learning is to increase the learning quality and efficiency, to facilitate a learner’s and a teacher’s work. We can distinguish two main directions of IT application in training: (1) if applying IT we strive to improve the traditional methods; (2) if new methods are developed that are applicable only if IT is used. In both cases, sharing the good experience of teachers and mastering of the learning methods are of great importance. The research work is meant for solving the problems of using methodological resources and learning methods, which arise due to insufficiency of information in the metadata repositories of learning object (LO). The main models of LO metadata standards, used to describe digital learning resources in a formal way, have been analyzed and compared. Scientific and practical principles for applied model design of LO metadata standards have been explored. The content LO developing models that ensure LO compatibility have been considered. The empirical research performed enabled us to determine a further trend of research and influenced the creation of an extended LO metadata applied model. The design process of a metadata applied model consists of the following phases: 1) determination of sets of metadata elements that describe methodological resources and learning method objects, 2) composition of controlled vocabularies, aimed at description of metadata elements, with a view to ensure the compatibility of metadata, 3) comparative analysis of metadata that describe methodological resources and learning method objects, 4) completion and implementation of the extended LO metadata model. The model proposed here was implemented in a prototype of the LO metadata repository, however there is a lack of data in it to carry out engineering experiments. Pilot metadata of methodological resources and learning method objects, created in the prototype, allowed us to test the prototype functioning and to make sure of its correctness. The expert estimation of model resulted in the conclusion that, after implementing the model proposed the access to digital learning resources is increased two times. This proves that digital learning resources become more accessible to users and more favorable conditions are created to use them in practice