Open AccessTHE ANALYSIS OF FUNCTIONAL COMPLETENESS OF THE ONLINE LEARNING SYSTEMS
Author(s) -
T. A. Shkodina
Publication year - 2020
Publication title -
vektor nauki tolʹâttinskogo gosudarstvennogo universiteta. seriâ èkonomika i upravlenie
Language(s) - English
Resource type - Journals
ISSN - 2221-5689
DOI - 10.18323/2221-5689-2020-4-56-64
Subject(s) - completeness (order theory) , computer science , ranking (information retrieval) , learning management , machine learning , artificial intelligence , data mining , mathematics , multimedia , mathematical analysis
Currently, there are many online learning systems, which support online learning management processes. However, it is rather hard to choose an e-learning management system on your own. The paper considers a comprehensive assessment method based on the use of the developed comparison algorithm and the algorithm for the optimal choice of complex e-learning management systems according to the functional completeness criterion. The study shows to what extent the e-learning management systems selected for comparison have similarities or differences in terms of functional completeness. The author analyzed whether they contain the most typical e-learning systems and what additional functions each of the compared systems has. The paper shows how it is possible to assess how the functional completeness of a particular system meets the user’s requirements. The developed comparison algorithm allows grouping the features of the considered complex e-learning management systems and highlighting the most significant functions or groups of functions. The study determined the degree of absorption of one complex system over another. The author carried out the ranking of the considered e-learning management systems according to the functional completeness criterion. To identify the system that is superior to the others and to determine the presence of the unique functions, the author constructed the graphs of similarity, absorption, and superiority of the considered systems with varying threshold values. This method allows evaluating and selecting such e-learning management systems that best meet the software requirements and, based on the recommendations received, choosing the most appropriate version of the online-learning management system, taking into account the user’s preferences.