РАЗРАБОТКА МЕТОДОВ ИНТЕЛЛЕКТУАЛЬНОГО РАНЖИРОВАНИЯ РЕЗУЛЬТАТОВ КОНТРОЛЯ ЗНАНИЙ С УЧЕТОМ АДАПТАЦИИ К ЦИФРОВОМУ ФОРМАТУ ОБУЧЕНИЯ МАТЕМАТИКЕ

Abstract

The article is devoted to the development of methods for the intelligent ranking of the results of knowledge control, taking into account adaptation to the digital format of teaching mathematics. Approaches to learning associated with the use of a hybrid intellectual learning environment are characterized, taking into account the conditions of distance learning. The features of the digital transformation of mathematical education are considered, taking into account the use of methods of intellectual analysis. Methods for intelligent ranking of intermediate results of knowledge control are proposed, taking into account adaptation to the digital format of teaching mathematics. The issues of adapting intelligent learning technologies to the distance form of implementation are considered. The article develops a ranking methodology using the idea of V.P. Bespal'ko about the representation of the structure of human activity in the form of successive levels of assimilation associated with the evolution of the student's experience. The ability to solve problems of various levels of complexity is determined by such levels of assimilation as student, model, heuristic, research. Taking into account this approach, it is possible to use various indicators of students' achievement of one or another level of assimilation of educational material. The necessity of an additional assessment of the activities of students in the conditions of distance learning and establishing the dependence of learning outcomes on procedural aspects is substantiated. Ranking is carried out on the basis of artificial intelligence technologies. To model the educational process, algorithms based on machine learning have been proposed, in particular, a generalized clustering algorithm based on the k-means method has been developed. The developed software is aimed at intellectual evaluation of the results of intermediate knowledge control and at identifying research potential. A series of computational experiments based on a probabilistic model has been carried out, and the interpretation of the results obtained has been given. The proposed models and algorithms are focused on the creation of such a methodology that helps to increase the efficiency of the pedagogical process, and also provides control and assessment of knowledge, taking into account the processes of digital transformation of education. The results of this study are of practical importance for the development of methods for assessing knowledge in mathematical disciplines in distance learning. The results can be used in the tasks of predicting the indicators of the pedagogical process, taking into account its digital transformation.