Subject domain modeling in adaptive learning systems with self-learning support

Abstract

Highly developed competencies, including those acquired through targeted self-education, produce marketable specialists, from whom employers expect continuous professional development. Such competencies can be acquired during university or even school education. The purpose of the article is to examine various aspects of developing a subject domain model in adaptive learning systems that support the development of self-learning skills. To obtain this result, we analyzed and summarized the results of experiments implementing adaptive learning systems in Russia and abroad. A software prototype of the system to confirm the feasibility of the proposed principles was created. An attempt is made to substantiate the need to stimulate the development of self-educational competence and, in this regard, to demonstrate the specifics of constructing a subject domain model. The relationship between the development of self-educational competence and learning in a digital educational platform (DEP) is examined. A diagram of the interaction between the components of the digital educational platform in the adaptive learning process supporting self-learning and a generalized algorithm for the system’s operation are presented. The correspondence of the proposed approach with the principles of L. S. Vygotsky’s zone of proximal development is outlined. The proposed principles for developing a domain model to support self-learning can be used to expand the functionality of existing adaptive learning systems and digital educational platforms. The authors offer a new perspective on the role of a modern learning automation system, which, in addition to automating typical routine actions, also contributes to the development of a personalized approach to self-learning for each student.