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Публікація An approach to the implementation of a competency-based approach in the learning management system(Національний авіаційний університет, 2023) Kopp, A. M.; Parashchych, Mykyta; Zviertsev, Herman; Motalyhin, Y. Y.; Strelnikova, AnnaThis paper solves the urgent problem of improving the tracking of the process of acquiring competencies by students through the means of analyzing the learning management system data and visualizing the results of the learning process. The object of the study is to track the process of acquiring competencies by students. The subject of the study includes software components for the implementation of a competency-based approach in the learning management system. The purpose of the study is to improve the tracking of the process of acquiring competencies by students by analyzing the data of the Learning Management System (LMS) and visualizing the results of the learning process. Thus, to achieve this goal, we analyzed the technologies for processing learning data from LMS, analyzed the features of modeling the learning process based on Petri nets and BPMN (Business Process Model and Notation), determined a data structure, and proposed an algorithm for building a model and visualizing the learning process data. The developed software components allow processing of learning process data from LMS, building models and visualizations of learning process data, saving the results to data warehouses, depicting the learning process model, and visualizing learning process data for further analytical processing.Публікація A Business Intelligence Dashboard Design Approach to Improve Data Analytics and Decision Making(CEUR Workshop Proceedings, 2020) Orlovskyi, D. L.; Kopp, A. M.This paper considers a problem of dashboard design in order to improve data analytics and decision making as business intelligence capabilities. Essentials of data warehouses and data marts used as data sources for business intelligence activities are briefly outlined, and the star schema data structure is considered as the most widely used. Data visualization is considered from the perspective of proper visualization graphs and charts selection. It is extremely vital for designed dashboards, since inappropriate visuals may mislead users and shift their focus to wrong things. Bar charts, line charts, and pie charts are considered as the most common visualization graphs. Proposed approach includes two phases: dataset preparation and dataset analysis. While dataset preparation is mostly focused on star schema transformation into flat structures, dataset analysis phase proposes recommendations on which visualizations may be placed on a designed dashboard. In order to propose such recommendations, threshold values of dataset sizes are used. A dashboard design process, which is considered as the baseline of the proposed dashboard design approach, is outlined. Sample dataset in considered, five data subsets are prepared and recommendations on visualization charts for these datasets, which may be placed on a dashboard, are proposed. Obtained results are discussed, conclusions are made, as well as the further research objectives in this field are formulated.