From LMS to adaptive training systems

Abstract

The use of information technology and, in particular, learning management systems, increases the ability of both the teacher and the learner to achieve their goals in the educational process. Such systems provide educational content, help organize and monitor training, collect progress statistics, and can also take into account the individual characteristics of each user of the system. The purpose of this study is to determine the direction of development of modern learning systems and technologies for their implementation. The evolution of learning management systems, the transition to intelligent learning systems, the main stages of such systems were reviewed, the types of learning sequences were analyzed, the transformation

into adaptive learning systems was identified, and the scheme of the system and its mathematical model were presented. Expertise systems, the theory of fuzzy sets and fuzzy logic, cluster analysis, as well as genetic algorithms and artificial neural networks are defined as the mechanisms for implementing the learning systems. An artificial neural network in an adaptive learning system will allow you to create a unique training program that will build on existing knowledge and the level of perception of educational material by students. By formalizing the intellectual processes that both the teacher and the student carry out, it is possible to automate a certain part of the teacher’s functions, reduce the cost of manual labor, which will make it easier to monitor the learning process and also make the learning process more efficient.