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Modelling and Data Analysis
2023. Vol. 13, no. 4, 153–164
https://doi.org/10.17759/mda.2023130409
ISSN: 2219-3758 / 2311-9454 (online)

Modeling Processes for Automated Generation of Work Programs

 
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Abstract

A method for formalizing educational text into an ontology is proposed. It is proposed to preserve the transmission of the meaning contained in the text by operating with minimal educational elements: definitions of specific entities, descriptions of its properties, actions performed, rules, formulas and similar fragments of knowledge. The formal structure representing the educational text, which can be considered as a directed graph, the vertices of which make up frames describing educational elements, provides the opportunity to develop models and algorithms that can effectively solve a number of problems in the field of education. The same structure makes it possible to develop a model of the content of a work program devoted to the study of knowledge contained in a given educational text.

General Information

Keywords: educational text, program, content, ontology, graph

Journal rubric: Method of Teaching

OpenAlex citations: 0

OpenAlex trends: Artificial Intelligence in Education, Information Systems and Technology Applications, Scientific Research and Philosophical Inquiry

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Number of citations: 0

Topics

Artificial Intelligence in Education

This cluster of papers explores the intersection of education and technology, focusing on topics such as artificial intelligence in educational systems, distance learning, depression diagnosis using neural networks and fuzzy logic, e-learning platforms, and pedagogical innovation. It also delves into the application of digital technologies in teaching and learning processes, knowledge management in educational settings, and the impact of digital transformation on education.

Number of works: 14182  |  Total number of citations: 18505

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Information Systems and Technology Applications

This cluster of papers focuses on the fundamentals, drivers, and business models of enterprise content management, including topics such as information management, machine learning, predictive modeling, web content management, artificial intelligence, service systems, big data analysis, and digital document management.

Number of works: 16253  |  Total number of citations: 26702

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Scientific Research and Philosophical Inquiry

This cluster of papers covers a wide range of topics related to information science and technology development, including the impact of digital technology, foresight methods, knowledge management, big data, innovation, media, ontology, and semantic search. The papers explore the intersection of information science with various fields such as economics, education, neuroscience, sociology, and environmental studies.

Number of works: 44007  |  Total number of citations: 112893

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Work details in OpenAlex

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2023130409

Received 24.11.2023

Accepted

Published

For citation: Verteshev, S.M., Voronov, M.V. (2023). Modeling Processes for Automated Generation of Work Programs. Modelling and Data Analysis, 13(4), 153–164. (In Russ.). https://doi.org/10.17759/mda.2023130409

© Verteshev S.M., Voronov M.V., 2023

License: CC BY-NC 4.0

References

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  3. Verteshev S. M., Voronov M.V, Gerasimenko, P. V., Kremkov, M. V. Prinyatie reshenii pri upravlenii organizatsionnymi sistemami: monografiya. ̶ Pskov: Pskovskii gosudarstvennyi universitet, 2019. 218s.
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Information About the Authors

Sergey M. Verteshev, Doctor of Engineering, Professor, Pskov State University (FSBEI HE PskovSU), Pskov, Russian Federation, ORCID: https://orcid.org/0000-0001-6696-3086, e-mail: verteshev@mail.ru

Mikhail V. Voronov, Doctor of Engineering, Professor, Head of the Department of Applied Mathematics, Faculty of Information Technology, Moscow State University of psychology and education, Leading researcher at the Laboratory of Computer Textbooks, Faculty of Further Education, Moscow State University. Lomonosov, Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-7839-6250, e-mail: mironovov@yandex.ru

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