Вісник № 01. Системний аналіз, управління та інформаційні технології
Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/47393
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Документ Developing adaptive learning management application for project team in It-industry(Національний технічний університет "Харківський політехнічний інститут", 2020) Sokol, Volodymyr Yevhenovych; Bronin, Sergiy Vadymovich; Karnaukh, Vira Eduardivna; Bilova, Mariia OleksiivnaKeeping employees aligned with modern trends and developments in their professional areas is the main focus of a lifelong lea rning approach. That becomes even more important for such dynamic industries like Information Technology. Therefore, it’s crucial to extend existing e-learning management system with an adaptive training component that enables the effective study of on-demand skills, leading to a broader range of candidates available for project management to select from and consequently improving the overall performance of an IT company. To improve the existing learning process according to company's and employee's needs the overview of a typical learning management system functionality is given in this paper. The main benefits from the adoption of a learning management system in small and medium-sized IT-companies were discussed, analysis of their features and problems was given. The adjustment plan for the typical learning management system to be suitable for the information technology domain including module of the adaptive learning content selection using the basic principles of graph theory was proposed to reduce the time of the learning process. LMS OpenOLAT was reworked according to the adjustment plan which is reflected by the number of diagrams such as sequence diagram, IDEF0 business process description, activity diagram that shows search algorithm steps and application component diagram. Also, GUI was adjusted to provide user with a good look and feel. The benefits of the proposed approach in business processes of IT-company are shown using “Academy – Smart”. To prove the efficiency of the proposed algorithm, real courses were used. Based on the learning material, provided by “Coursera”, a number of test cases was formed and analyzed. After applying adaptive content selection algorithm according to the models of “Academy – Smart” employees, learning time was reduced and optimized. This investigation has shown significant improvement in the resource management process and acceleration of the learning process for employees.