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Digitization is one of the key factors in the development of the modern educational system. Using end-to-end digital technologies in the educational process leads to the accumulation of a large amount of data on students’ behavior and learning outcomes in the digital educational environment. The analysis of these data will enable educators to improve the efficiency and quality of students’ learning. The article analyzes the correlation between learning success and students’ behavior in the university digital educational environment employing the methods of educational analytics. The research relied on theoretical, empirical, and mathematical methods. We provided a definition of educational data and explain their intended purpose. Next, we described the methods used to analyze educational data and gave examples of applying models based on them in the education sector. We developed and demonstrated a model of the correlation between students’ final grades and their activity during university training using the example of an online programming course hosted on the Moodle LMS platform. Impact analysis was carried out both for individual indicators and for their combination. As a result, the research has identified a student’s actions that create the most significant impact on the final score. The model can be used to predict students’ learning success in the digital educational environment based on their activity and learning outcomes in order to improve the managerial effectiveness of the learning process at universities.
Toktarova et al. (Mon,) studied this question.