Article

Article title KNOWLEDGE LEVEL AND DECISION SUPPORT ANALYSIS FUZZY MODELS DURING EDUCATIONAL PROCESS
Authors Yu.A. Kravchenko
Section SECTION III. ARTIFICIAL INTELLECT AND INDISTINCT SYSTEMS
Month, Year 07, 2014 @en
Index UDC 002.53:004.89
DOI
Abstract Article is devoted to the development of the subject’s knowledge level analysis fuzzy models, allowing you to determine the presence and degree of the necessary professional competencies formation. Using of the fuzzy modeling methods will take into account the natural processes associated with the loss of some knowledge for a long time period and create a valid predictive model of residual knowledge in long-term memory. Also the possibility of fuzzy modeling in support of decision-making problem in the formation of individual learning paths was considered. The feature of the training system’s nonlinear structure requiring intellectual approach to the planning of the educational process throughout its duration was noted. The paper considers the development of approaches to building a specialized fuzzy models represent diverse subject knowledge for intelligent information systems in the face of uncertainty with a detailed study approaches handle different parts of heterogeneous domain knowledge. Under heterogeneous knowledge refers to all substantive expert knowledge about the composition and structure of the electronic resource that is represented in the intellectual knowledge management system in order to obtain the required level of learner competency components in this area of expertise. Adaptive learning process requires planning educational effects based on a combination of diverse subject knowledge, existing competencies and individual characteristics. The article also describes the fuzzy model analysis of the subject knowledge allowing level to determine the presence and degree of the necessary professional competencies formation. Using the methods of fuzzy modeling takes into account the natural processes associated with the loss of some of the knowledge for a long period of time and create a valid predictive model residual knowledge in long-term memory. Also considered the possibility of fuzzy modeling in support of decision-making on the formation of individual learning paths.

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Keywords Fuzzy models; intelligent educational systems; assessment of competence; knowledge management systems; decision support.
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