Bozhday Aleksandr Sergeevich, Doctor of engineering sciences, professor, sub-department of CAD, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Evseeva Yuliya Igorevna, Postgraduate student, Penza State University (40 Krasnaya street, Penza, Russia), firstname.lastname@example.org
Background. Development of adaptive software applications with an extended life cycle is one of the most promising directions in the software engineering industry. The world of modern educational technologies is not an exception. Training program design should be based on fast variability of the student's characteristics (continuous improvement of their knowledge and skills) as well as the environment (changes in educational standards, requirements, technical capabilities). In this case, the learning process should not be interrupted because of the software renovation. The basis of a training program should be represented by such a model that would allow the program to track the processes of environmental variability and adapt itself to them without having the source code recompiled. The main objectives of the work are as follows: 1) to provide an overview of the existing variability technologies and self-adaptive software; 2) to consider the question of training software life cycle extending; 3) to offer the variability modeling technology in the processes of automated adaptive training programs design with support of 3D-graphics.
Materials and methods. There authors used variability modeling methods on the basis of feature diagrams and their formal propositional representation, as well as the software product line technology.
Results. The authors completed the review of adaptive systems as the most promising variety of computer training programs; the article describes the basic strategies of adaptability. The existing training software synthesis tools based on artificial intelligence and adaptability were studied. The basic disadvantages of these systems were found, and the methods of solving thereof were proposed. The problems of variability modeling of subject areas and program environment were considered. The use of the variability technology in computer-aided design of training software was proposed. The authors also investigated the possibility of using the technology in creation of e-learning courses.
Conclusions. The described modeling technology allows to design self-adapted learning applications, which are able to offer increasingly sophisticated modeling and learning situations in the course of interaction with a user. These situations are not created in advance by programmers; they are generated promptly on the basis of the feedback from users and the environment. The authors have offered an opportunity to create a tool for the synthesis of the training software that can independently maintain and extend its life cycle. Low entry barrier of this platform opens up opportunities to create educational applications for those who have no special training in the field of information and computer technologies.
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