Multifactor classification technology of mathematical content of e-learning system

The article continues the study of the problem of classifying the content of an e-learning system. The previously developed technology for thematic classification of mathematical content contained in the blocks of tasks and examples of e-learning system has been improved and supplemented with new functions. For this purpose, the previously used content model with two properties — a text description of a task and its formula part in \TeX format — has been supplemented with a number of formal numerical attributes, such as the presence of transcendental and derived functions, and the number of formulas in the task. This block of attributes made it possible to improve the quality of the existing thematic classifier and to implement two new ones. The first classifier determines the level of complexity of the task. The second multilabel classifier determines the set of student competencies that the task should form. Such a multifactorial classification is an important stage in the promising direction of the development of e-learning system — automated assessment of the quality of educational content. Performance testing of the proposed algorithms, training of classifiers, and analysis of classification quality were carried out using the tasks from the same discipline of the theory of functions of a complex variable but on significantly expanded set of data, including tasks for independent work of students — calculation and examination tasks.