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Over the past decade, online learning technologies have become widespread in the non-formal education, higher education and additional vocational training sectors. The best Russian and foreign universities produce digital content and create online courses that are used not only by students of these universities, but also by other educational organizations for the implementation of their educational programs. Digital platforms that host online courses allow monitoring and logging of every step of learners and their achievements, while mastering a course and passing current tests and final exams. This creates the prerequisites for developing adaptive learning systems that adapt to each learner, determine their level of knowledge, track behavioral patterns, learning styles, and automatically organize content that enables achieving the best learning outcome. The study is aimed at analyzing the behavioural patterns of students while mastering massive open online courses. For this purpose, six online courses created by two universities were studied: Ural Federal University and National University of Science and Technology (MISiS). All the courses are hosted on the National Open Education Platform (Russia), which is based on edX open-source platform. To analyze the behaviour patterns, logs of students’ activity on the platform were examined. Using the IP addresses the data was normalized by time zones. Different types of student interaction were explored with the content throughout the courses and the peculiarities of student's work with different components of the courses were described. During the study some typical temporal patterns of students’ behaviour were revealed and analyzed in conjunction with their success rate. The findings of the research may be useful to the authors of the courses for improving the content, as well as to the tutors for supporting learners during training or education programmes. © The Authors, 2019. All Rights Reserved.