Intelligent analysis of the quality of educational content on statistics of student performance in the learning management system "Scorina"
https://doi.org/10.37661/1816-0301-2021-18-2-58-71
Abstract
The article provides the analysis of the advantages and disadvantages of distance education, the specifics of educational process and the use of educational content for this form of education. The problems of assessing the quality of educational content for the distance educational process and its effectiveness are determined. The structure of the developed learning management system "Scorina" and the mechanisms for creating educational content, the learning process, attestation of students and the collection of progress statistics are described. A mathematical model of educational process of learning management system "Scorina", and approach to assessing the knowledge of students are presented.
The implementation of functional diagram and the algorithm of the module for the intelligent analysis of the quality of educational content of learning management system "Scorina" is proposed. The module is designed to identify the shortcomings in educational content and to improve the materials that could cause the difficulties for students when studying certain issues or topics of the disciplines are studied based on statistical data of student performance. The connection of specific parts of educational content with specific questions of control tests is implemented through special labels created during the development of the content of the studied disciplines. The mining algorithm allows to identify and exclude from the statistical sample the information of the students whose academic performance characteristics are not objectively related to the quality of educational content.
About the Author
A. G. SavenkoBelarus
Andrei G. Savenko - Postgraduate Student, Senior Lecturer, Department of Information Systems and Technologies, Faculty of Computer Technologies, Institute of Information Technologies of the Belarusian State University of Informatics and Radioelectronics.
st. Kozlova, 28, Minsk, 220037.
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Supplementary files
Review
For citations:
Savenko A.G. Intelligent analysis of the quality of educational content on statistics of student performance in the learning management system "Scorina". Informatics. 2021;18(2):58-71. (In Russ.) https://doi.org/10.37661/1816-0301-2021-18-2-58-71