ORGANIZATION, DEVELOPMENT AND IMPLEMENTATION OF INTELLIGENT LEARNING ENVIRONMENTS

Making complex computer-based information systems of various domains more intelligent enhances their efficiency, first of all, through using and processing the knowledge. Today the methods and means of artificial intelligence are widely used to design such systems. The purpose of our research is to research, design and implement the complex computer-based training systems that are intelligent learning environments (ILEs). To accomplish this purpose we should solve the following tasks: 1 We should analyze the intelligent computer-based learning systems. 2 We should develop the architecture, methods, models and algorithms of ILEs for universities and enterprises. 3 We should develop software and data support for ILEs. 4 We should summarize the experience of ILE implementation and utilization. In the frame of the first task we have examined expert-training systems and adaptive training systems. Expert training systems are based on the integration of computer-based learning technologies with expert systems. Expert-training systems are designed to solve ill-structured problems. They use standard general knowledge and knowledge acquired by students. Individual dynamic learning path is based on the logical conclusions. Adaptive training systems implement feedback between a learner and a system that is used to manage the educational process. Methods and models of the theories of neural networks, graphs, fuzzy sets, classifications, agent systems, and others are used to create individual learning paths. The complex information and communication system with internal and external sources of knowledge, and intelligent sensors has been developed to solve the second problem. We have proposed the approach to create ILEs, which is based on the principles of formal and informal learning integration, personalized learning, the formation of competency based on training and "real" knowledge (real knowledge means the experience of enterprises and companies of the real economy as hybrid knowledge bases), the active utilization of simulators, virtual worlds and augmented reality. To implement the principles (the third task) we have proposed a number of models and methods: 1 an associative dynamic multilevel domain model; 2 an overlay learner model; 3 a model of scenario of learning process is based on step-by-step representation of industrial items development structure and process; 4 a method of controlling and diagnosing learner's qualimetric characteristics; 5 a method of generating the dynamic adaptive personalized path of a learner; 6 a method of integration of based learning platform with social networks and online learning technologies. We have developed a system of virtual simulators, which is part of ILEs and it is used for training programs in radio engineering, instrument engineering, and computing techniques. The system is based on an automaton approach, and the expert evaluation system of student actions is implemented into it. The Institute of Distance and Further Education of UlSTU (Russia) has developed the above mentioned products on the platform Moodle. ILEs have been implemented into the educational process of UlSTU and a number of industrial enterprises of the Ulyanovsk region. We have summarized the experience of the use of ILEs. The ILEs implementation has increased the quality of education.