On the issue of educational and methodological information selection for implementing an adaptive learning management system: Algorithm of selecting authors of literature taking into account the emotional and psychological characteristics of users based on the ideas of academic genealogy
Year: 2025
Type: article
Abstract: The article is devoted to the development of a new algorithm for integrated distributed information systems, which should ensure the selection of authors of scientific and educational-methodical literature and the literature itself, taking into account the emotional and psychological characteristics of the system users based on the ideas of academic genealogy. The need to create such an algorithm is due to the fact that the currently actively developing process of transition to an information society, observed in various spheres of society, leads to quite strong changes in the field of economics, employment of the population, education, information systems for providing information. While the core of these transformations is the use of information and educational digital platforms that are adaptive to the emotional and psychological characteristics of students. The key factor that determines their success is the algorithm for selecting scientific and educational-methodical literature, taking into account the individual characteristics of students. Educational and methodological information is usually formed on the basis of new scientific results obtained during the implementation of dissertation research, while the volume of materials used in them is steadily growing according to a law close to exponential. Accordingly, the requirements for integrated distributed information systems (electronic library systems) that support the educational process are sharply increasing, which requires the creation of a fundamentally new algorithm. The article lists limitations and recommendations for the practical implementation of the algorithm proposed in the work.
Source: Informatics and Education
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4412899693