THE METHODOLOGY OF CREATING AN INTELLECTUAL ENVIRONMENT OF INCREASING THE COMPETENCE OF STUDENTS BASED ON A BAYESIAN APPROACH

Abstract

Artificial intelligence is widely used in solving various problems in various fields of science. The actual use of artificial intelligence methods to create an intellectual environment to improve the competence of the student. Recently, research into the most popular use of artificial intelligence has been the use of Bayesian network apparatus. When creating an intellectual environment for improving the competence of a student, the Bayesian approach is promising. At present, the theory of Bayesian networks is used in various fields of science and production in solving various applied problems. There is a fairly large number of software products for working with Bayesian networks. These products are divided into commercial and free. To implement the mathematical ideas of the Bayesian network, the BayesiaLab application software package is well applied and is one of the high-quality software products that specializes in artificial intelligence technologies. With the help of the package BayesiaLab, you can explore, edit, analyze and determine the model of the Bayesian network. This article provides definitions of various scientists to the term "competence" and explores the possibilities of using Bayesian networks in the formation of students' competence in the direction of information technology. For the formation of students' competencies in the field of information technology, a generalized algorithm and a general architecture of the intellectual environment have been developed. In order to improve professional competence in education, it leads to an increase in the competitiveness of specialists, an improvement in the content, methodology, and updating of the corresponding educational environment. In the formation of competence, a number of technologies are applied: cognitive-oriented, activity-oriented, personality-oriented. The approach used in the formation of competencies is used to simulate the quality of student knowledge. The level of competence depends on the method chosen.