Применение методов нечеткой логики для формирования адаптивной индивидуальной траектории обучения на основе динамического управления сложностью курса
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Use of fuzzy logic to create an adaptive individual learning path based on dynamic course complexity management

idBelov M.A., idGrishko S.I., idZhivetyev A.V., idPodgorny S.A., idTokareva N.A.

UDC 510.676, 519.7
DOI: 10.26102/2310-6018/2022.39.4.018

  • Abstract
  • List of references
  • About authors

The article presents a model for creating an adaptive individual learning path based on dynamic control of the course complexity using fuzzy logic methods. The model helps to individually manage the complexity of the training course for each student and to formalize the process of solving practical tasks and feedback from students motivating them to study productively taking into account personal characteristics and preferences. Implementation of such models and corresponding systems in the training process enables teachers to choose the most appropriate tasks for each student with due regard for individual characteristics and personality. The approach allows teachers to allocate more time for scientific, methodological and creative work, especially with the option to distribute educational materials in the form of microlearning, where a large number of students, usually studying online, is invited to perform many small practical tasks. Also, adaptive learning paths are designed to promote the development of adaptive thinking and adaptive strategies for students behavior. The individual learning path is an important element of online learning management system in the cloud environment of "Virtual Computer Lab" educational data center created by M.A. Belov (https://belov.global) in 2007 at the Institute of System Analysis and Control of Dubna State University, the hallmark of which are the principles of self-organization.

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3. 3. Belov M.A., Grishko S.I., Cheremisina E.N., Tokareva N.A. Training IT specialists in a global digital transformation. The concept of automated management of competency profiles in educational programs of the future. Sovremennye informatsionnye tekhnologii i IT-obrazovanie = Modern information technology and IT education. 2021;17(3):658–669. DOI: 10.25559/SITITO.17.202103.658-669. (In Russ.).

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12. 12. Cheremisina E.N., Belov M.A., Antipov O.E., Sorokin A.V. Innovative practice of computer education at Dubna University using a virtual computer laboratory based on cloud computing technology. Programmnaya inzheneriya = Software engineering. 2012;5:34–41. (In Russ.).

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14. 14. Cheremisina E.N., Belov M.A., Lishilin M.V. Integration of a virtual computer laboratory and a knowledge space is a new look at the training of highly qualified IT specialists. Sistemnyi analiz v nauke i obrazovanii = Systems analysis in science and education. 2014;1(23):97–104. (In Russ.).

15. 15. Sidorov D.S., Belov M.A. Design of hardware and software systems in the educational process with the use of a virtual computer laboratory. Sistemnyi analiz v nauke i obrazovanii = Systems analysis in science and education. 2020;2:70–82. (In Russ.).

Belov Mikhail Aleksandrovich
Candidate of Technical Sciences

WoS | Scopus | ORCID | eLibrary |

Dubna State University

Dubna, Russian Federation

Grishko Stanislav Ivanovich

ORCID |

Dubna State University

Dubna, Russian Federation

Zhivetyev Aleksandr Viktorovich

ORCID |

Dubna State University

Dubna, Russian Federation

Podgorny Sergey Aleksandrovich
Doctor of Technical Sciences, Professor

ORCID |

Dubna State University

Dubna, Russian Federation

Tokareva Nadezhda Aleksandrovna
Candidate of Physical and Mathematical Sciences, Associate Professor

ORCID |

Dubna State University

Dubna, Russian Federation

Keywords: IT education methodology, distance learning, individual learning path, digital transformation, microlearning, fuzzy logic, virtual computer lab

For citation: Belov M.A., Grishko S.I., Zhivetyev A.V., Podgorny S.A., Tokareva N.A. Use of fuzzy logic to create an adaptive individual learning path based on dynamic course complexity management. Modeling, Optimization and Information Technology. 2022;10(4). URL: https://moitvivt.ru/ru/journal/pdf?id=1249 DOI: 10.26102/2310-6018/2022.39.4.018 (In Russ).

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Full text in PDF

Received 24.11.2022

Revised 03.12.2022

Accepted 27.12.2022

Published 31.12.2022