Application of the convergent education model in the development of a smart learning environment

The article presents a scientific and practical approach to the development and implementation of the concept of convergent learning in the framework of building an open educational platform to manage the process of training specialists. The presented concept of convergence education is based on the integration of educational programs, learning content, competency matrices, methods and technologies for training specialists and personalized learning trajectories in smart learning environment. To implement the model and the convergent approach, it is vital to make use of an information and educational environment with mechanisms to support convergent learning based on regional labor market analysis, actualizing of educational programs and resources, harmonization and synchronization life-cycle models thereof, adaptive customization and personalization of specialist training trajectories. The article presents the developed convergence model of educational programs and employer vacancies as a weighted graph to illustrate the relationship between competence requirement vectors of educational programs and sought-after employment. To isolate the convergence model components and evaluate the convergence degree thereof, a graph clustering algorithm based on the Louvain method has been developed. A method for synthesizing a convergence model of educational content organized as a fuzzy weighted graph has been presented, and sets of topics and sections of electronic learning resources being its vertices. Search and extraction of convergence educational content sections have been implemented by means of an algorithm for extracting fuzzy isomorphic subgraphs, and assessing the convergence degree thereof. The results of the study are used to synthesize an information and educational environment with intelligent mechanisms for supporting learning processes based on an analysis of the requirements of labor markets and actualizing educational content and training programs, as well as adaptive customization and personalization of specialist training trajectories. The architecture of the educational environment includes a set of software and tools for managing the components of the information space of the university with support for mobile, cloud and blended learning technologies.