ЭФФЕКТИВНЫЕ ОБРАЗОВАТЕЛЬНЫЕ ПРАКТИКИ НА ОСНОВЕ АЛГОРИТМОВ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ПОДГОТОВКЕ БУДУЩИХ ПЕДАГОГОВ

Abstract

The paper considers practical aspects of the implementation of the educational process in an electronic educational environment for students — future teachers in order to form their readiness to perform work functions and actions in conditions of uncertainty and digital transformations. Based on the analysis of scientific literature, the results of the survey, the experience of preparing students of pedagogical directions, as well as taking into account the application of a multi-paradigm approach to pedagogical education, the methods of training future teachers using artificial intelligence algorithms are proposed. The article presents the methodology of the existence and functioning of a collective pedagogical megasystem, both forecasting pedagogical processes and identifying new patterns and making effective didactic decisions based on the use of collective intelligence algorithms in the implementation of pedagogical practice. The article reveals the applied aspect of the use of collective intelligence algorithms in the implementation of quasi- professional activities at the university and during pedagogical practice in order to form the readiness of future teachers to implement pedagogical activities based on learning to choose effective didactic solutions. This aspect is key for the readiness and ability to implement professional actions and functions due to variations: the contingent of students, subject content, organizational and pedagogical conditions of a particular educational organization. Taking into account both spontaneous and systemic aspects in the implementation of professional activity is crucial for the choice of learning technologies that ensure maximum productivity of the teacher and, as a result, the achievement of high educational results of students. For these purposes, the most suitable algorithm for choosing methods and technologies for the implementation of professional activities by future teachers is the ant algorithm. This algorithmic model allows us to take into account both the probabilistic nature of the changing impact parameters, and allows us to evaluate and select the high effectiveness of the application of this algorithm, which distinguishes it favorably among other artificial intelligence algorithms. The article provides an example of an ant algorithm for determining the best hierarchy of organizational and pedagogical conditions conducive to the best choice of technologies and methods for the implementation of professional activities by future teachers. As a conclusion, the authors propose to use collective intelligence algorithms in the process of quasi-professional activity of future teachers in the framework of pedagogical practice, which will contribute to the formation of their readiness to implement pedagogical activities in terms of performing labor functions and actions based on learning to choose effective didactic solutions.