infojournalИнформатика и образованиеInformatics and education0234-04532658-7769Publishing House Education and Informatics10.32517/0234-0453-2024-39-3-29-43infojournal-1093Research ArticleИНФОРМАТИЗАЦИЯ ОБРАЗОВАНИЯINFORMATIZATION OF EDUCATIONАрхитектура системы интеллектуального анализа компетенций для актуализации образовательных программ вузаThe architecture of the system of intelligent analysis of competencies for updating university educational programshttps://orcid.org/0000-0003-0876-3566ДеевМ. В.DeevM. V.

Михаил Викторович Деев, канд. тех. наук, зам. началь­ника отдела

Центр мультимедийных технологий и онлайн-обучения; отдел программирования и администрирования образовательных ресурсов

Пенза

Mikhail V. Deev, Candidate of Sciences (Engineering), Depu­ty Head of the Department

Center for Multimedia Technologies and Online Learning; Department of Programming and Administration of Educational Resources

Penza

miqz@yandex.ruПензенский государственный университетРоссияPenza State UniversityRussian Federation2024240820243932943Copyright © Деев М.В., 20242024Деев М.В.Deev M.V.This work is licensed under a Creative Commons Attribution 4.0 License.https://info.infojournal.ru/jour/article/view/1093

   Проблема актуализации образовательных программ и образовательного контента тесно связана с необходимостью их адаптации к меняющимся условиям региональных рынков труда. Решение этой проблемы достигается посредством сбора и анализа данных о компетентностных требованиях работодателей к квалификации специалистов (сами данные можно извлечь из объявлений о вакансиях на открытых ресурсах в сети Интернет). В статье представлен метод использования поисковых роботов и модулей обработки текстовых данных для получения формализованных описаний компетентностных требований и сравнения их по степени сходства с описаниями компетенций из образовательных программ. Для сравнительного анализа компетентностных требований разработан метод кластеризации с использованием аппарата нечеткой логики и нейронной сети. Архитектура системы сбора и интеллектуального анализа вакансий включает в себя поисковые краулеры, модуль парсинга текстовых данных с очисткой от информационных шумов, модуль консолидации данных, модуль генерации словаря ключевых слов, модуль синтеза векторов компетенций, модуль кластеризации, распределенный реестр формализованных описаний компетенций и др. Результаты сравнительного анализа необходимы для оценки соответствия компетенций специалистов, подготавливаемых в региональных вузах, требованиям работодателей в регионах. Проведенная оценка позволяет выработать рекомендации для актуализации образовательных программ и образовательного контента учебного заведения, а также провести адаптивную на­стройку компонентов информационно-­образовательной среды вуза.

   The problem of updating educational programs and educational content is closely related to the need to adapt them to the changing conditions of regional labor markets. The solution to the problem is achieved through the collection and analysis of data on the competence requirements of employers for the qualifications of specialists (the data itself can be extracted from job advertisements on open resources on the Internet). The article presents a method of using search robots and text data processing modules to obtain formalized descriptions of competence requirements and compare them by degree of similarity with competence descriptions from educational programs. For a comparative analysis of competency requirements, a clustering method was developed using fuzzy logic and a neural network. The architecture of the collection and intelligent analysis system includes search crawlers, a module for parsing text data with cleaning from information noise, a data consolidation module, a keyword dictionary generation module, a module for synthesizing competency vectors, a clustering module, a distributed registry of formalized descriptions of competencies, etc. The results of the comparative analysis are crucial for assessing the compliance of competencies of specialists trained in regional universities with the requirements of employers in the regions. The assessment allows to develop recommendations for updating educational programs and educational content of an educational institution, as well as to carry out adaptive adjustment of information and educational environment components of higher educational institutions.

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The authors declare that there are no conflicts of interest present.