The Technology of the Learning Process Management Expert System in Higher Educational Institutions

  • Authors

    • Batyrkhan Kuzenbaev
    • Rosamgul Niyazova
    • Ayzhan Kuzenbaevа
    2018-09-27
    https://doi.org/10.14419/ijet.v7i4.7.20563
  • expert system, learning process, ontology, higher educational institution, management, knowledge base

  • Abstract

    The present paper considers the development of learning process management expert system in higher educational institutions, based on the ontological approach. The purpose of research is an improve the effectiveness of decision making during the management of learning processes by using intelligent management methods and modern approaches to knowledge modelling. The methodology of solving the set task is based on models and methods of knowledge representation usage, the artificial intelligence theory, expert methods of decision-making and general theoretical principles of the control theory, and the theory of decision-making. Authors conducted a qualitative analysis of the domain knowledge, which allowed distinguishing and formalizing main concepts and relations between them. Authors suggested a methodological approach to the construction of the learning process management system, which allows implementing knowledge-based approaches to the development of information systems in the domain knowledge of learning process management. Authors also developed the structure and formal description of the ontology of the learning process in higher educational institutions, which allows reusing the suggested solutions. Research results were implemented in the expert information system; they can be used in practice in learning process management in higher educational institutions.

     

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  • How to Cite

    Kuzenbaev, B., Niyazova, R., & Kuzenbaevа, A. (2018). The Technology of the Learning Process Management Expert System in Higher Educational Institutions. International Journal of Engineering & Technology, 7(4.7), 283-291. https://doi.org/10.14419/ijet.v7i4.7.20563

    Received date: 2018-09-29

    Accepted date: 2018-09-29

    Published date: 2018-09-27