EDUCATIONAL ANALYTICS IN UNIVERSITIES: TOOLS FOR ANALYSIS AND FORECASTING

Abstract

Digital tools for data analysis play an important role in improving and optimizing processes in various fields of activity. A wide range of collected data increases interest in educational analytics to support effective management decision-making at all levels in higher education institutions. In this regard, educational institutions are using digital tools for analysis and forecasting that receive data from the learning management system (LMS) used by universities and provide summarized data in an appropriate format for each group of stakeholders. This article presents digital tools for processing large amounts of educational data accumulated on university platforms such as the Moodle LMS. This study identifies and describes three groups of educational analytics tools for e-learning courses (ELCs) developed on the basis of the Moodle LMS platform. The authors have developed an implementation scheme that includes the process of researching, cleaning, transforming and modeling large amounts of data obtained from the digital educational environment of an educational institution in order to identify hidden patterns, unknown correlations and visualize the necessary information. The article presents a diagram of the components of the system for conducting educational analytics based on Moodle big data and business intelligence systems such as Power BI, which allows creating interactive dashboards based on educational indicators. Using the standard analytical capabilities of Moodle and tools, an experimental study was conducted on the example of the educational portal of the National University of Life and Environmental Sciences of Ukraine, which allowed us to analyze which e-learning materials within educational programs are most popular, how timely students upload their work, what is the student engagement rate in an e-course, or which students potentially will not be able to complete their e-learning on time.