INTELLECTUAL DECISION SUPPORT SYSTEMS IN THE HIGHER EDUCATION INSTITUTIONS: OPPORTUNITIES AND LIMITATIONS

The article examines application of the intelligent decision support systems (IDSS) in higher education institutions. The general characteristics of the decision support systems are given, their main types, the most promising approaches and methods in the current situation are highlighted. A correlation is established between the main functions (subsystems) of the management and the most effective methods of IDSS for their implementation. Scenario and situation analysis, simulation modeling, the use of neural networks, and interactive dialog systems are considered among the best methods of IDSS. Special attention is paid to solving weakly structured (fuzzy) problems, for which it is optimal to supplement machine methods with the abilities of the human mind. The strengths of the IDSS are indicated: saving specialists’ working time, speeding up the decision-making process, and reducing the number of possible errors. At the same time, the limited opportunities of IDSS in the field of education are revealed, due to the uncertainty and multi-variant elements of management tasks, the priority of the human factor, and the importance of an individual approach to students. Among the specific tasks and approaches implemented with the use of IDSS, the following are indicated: achieving maximum efficiency in the use of the university resources (personnel, scientific, material), forming an optimal educational process (including individual combinations of training modules), achieving effective interaction with the external environment (scientific organizations, commercial enterprises). The importance of inter-university interaction and the organization’s participation in joint scientific and practical projects is emphasized, which also requires the use of IDSS. Further development of IDSS is possible on the basis of expanding the capabilities of the artificial intelligence, implementing the main requirements for IDSS, including: interactivity, adaptability (flexibility), semiotic, high-quality visualization, distributed and parallel information processing.

management, higher education, management solutions, intelligent accounting systems, information technology, situational analysis, neural networks, fuzzy problems, unstructured solutions, decision support systems, information processing.

Vaschenko V. A. Intellectual decision support systems in the higher education institutions: opportunities and limitations. Business. Education. Law, 2020, no. 4, pp. 224–229. DOI: 10.25683/VOLBI.2020.53.477.