Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
cетевое издание
issn 2310-6018

ADAPTIVE AUTOMATED SYSTEM AS A TRAINING DIFFERENTIATION MEANS IN THE INFORMATION TECHNOLOGY SPECIALISTS EDUCATION PROCESS

Datsenko N.V.   Gorbatenko S.A.   Gorbatenko V.V.  

UDC 004.9, 37.04
DOI: 10.26102/2310-6018/2019.25.2.007

  • Abstract
  • List of references
  • About authors

One of the most effective ways to implement a differentiated approach in the information technology (IT) specialists training which consists in the adaptive automated learning system use is proposed in the article. The system will allow to store a large amount of educational information, to modify it if necessary, to adapt it to different categories of users in accordance with their level of initial training, to check the formation of competencies and analysis of mistakes made by students in the control testing process. The system dataware includes a relational database (DB), which contains theoretical information of the discipline, exercises and control tasks on all topics, adapted to different categories of students, as well as a table in which all erroneous answers of users are entered during the control testing for further analysis. The software contains the users automatic classification module which is based on the cluster analysis method and allows at the input control stage to form four groups of students depending on the level of residual knowledge obtained in the previous disciplines study, corresponding to the marks as "excellent", "good", "satisfactory" and "unsatisfactory", in order to differentiate the educational material. The training program module is designed to solve the problems of new knowledge acquiring by students of different groups, using the theoretical knowledge obtained in the practical tasks implementation and checking the competence formation level. In the event that the level has not reached the baseline, the error analysis module allows to determine which discipline subjects have caused the greatest difficulties for the student to restudy.

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Datsenko Natalia Valerievna
Candidate of Technical Sciences
Email: natdatsenko@mail.ru

Voronezh State University of Engineering Technologies

Voronezh, Russian Federation

Gorbatenko Svetlana Alexandrovna
Doctor of Technical Sciences
Email: sv_gorbatenko@mail.ru

Voronezh State Institute of Physical Culture

Voronezh, Russian Federation

Gorbatenko Vladimir Valentinovich
Candidate of Physical and Mathematical Sciences
Email: vlgorbatenko@mail.ru

Voronezh State Technical University

Voronezh, Russian Federation

Keywords: training differentiation, it disciplines, improving the training quality, adaptive automated system, automatic classification, cluster analysis

For citation: Datsenko N.V. Gorbatenko S.A. Gorbatenko V.V. ADAPTIVE AUTOMATED SYSTEM AS A TRAINING DIFFERENTIATION MEANS IN THE INFORMATION TECHNOLOGY SPECIALISTS EDUCATION PROCESS. Modeling, Optimization and Information Technology. 2019;7(2). Available from: https://moit.vivt.ru/wp-content/uploads/2019/05/DatsenkоSoavtori_2_19_1.pdf DOI: 10.26102/2310-6018/2019.25.2.007 (In Russ).

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