2020
Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/44964
Переглянути
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.Документ Using cloud platforms to build distributed learning management systems(Національний технічний університет "Харківський політехнічний інститут", 2020) Sokol, Volodymyr Yevhenovych; Sapronov, Pavlo Yuriiovych; Bilova, Mariia OleksiivnaDistributed systems have problems with downtime, data loss during malfunctions, scalability and efficient use of computing resources. At the same time in the learning and training process, the use of a distributed system has the advantage of data processing: storage of information about students, construction of training courses, verification of passed material, etc. The problems of scaling and efficient use of resources in distributed learning management systems are investigated in this research. Cloud platforms for hosting the system, such as Amazon Web Services, Microsoft Azure, Google Cloud Platform and DigitalOcean are reviewed. Problems and features of a scalability in cloud computing are discussed. Methods, scaling and load balancing algorithms for the efficient use of computing resources are proposed. According to the list of advantages, the DigitalOcean platform was selected for the investigation. DigitalOcean provides cloud servers that can be used for quick creation of the new virtual machines for the projects. These servers allow to fully control the web hosting environment at the same time that the user pays only for the resources used. The main goal of DigitalOcean is to use a solid-state drive (SSD) to create a user-friendly platform that will allow clients to migrate projects to and from the cloud, increasing productivity with high speed and efficiency. As a result of analyzing information on existing technologies, approaches and methods for using cloud platforms in distributed systems, they have been applied to develop a solution to reduce downtime for a distributed adaptive Learning Management System (LMS). It is concluded that the use of cloud platforms for the construction of distributed LMS a practice that allows to use only the required amount of computing capacity. It is proven, that the implementation of the proposed solution into the work of adaptive LMS will improve its efficiency by reducing the time of the content delivering.