The article deals with methods and methodology of pedagogical research in the didactics of informatics in the environment of the Massive Open Online Course (MOOC) based on the principles of connectivism, which offers open, non-formal, and community education. The MOOC was created as a support for the implementation of pedagogical research (primarily for final theses), specifically for solving a causal research problem, which is the most challenging research issue in pedagogical research. We found that the created MOOC is didactically effective for all study degrees. We also identified the parts of the course (which correspond to the stages of processing the experiment) causing the participants the biggest problems. The surprising finding was that the data understanding (data exploration phase) causes the problem the most. Its importance was underestimated when designing the MOOC. Although this phase is the least computationally demanding, it is very important since it is subsequently related to the correct determination of the null statistical hypotheses.

Nowadays, education is a complex process that has many advantages. This is obvi-ously proven, as there are high demands on skills in today’s world. Therefore, it is a good approach to acquire this knowledge during the studies. Therefore, the re-quirement is aimed at the constantly improving and acquiring new experiences. In order to meet as many of these parameters as possible, it is important that we have an appropriately structured environment for students. The teaching process can be interpreted in several ways. In our research, we focus mainly on teaching through e-learning systems. Obviously, these supporting systems have many advanced func-tionalities to help make the whole learning process much easier to understand. In our work, we focus on methods and approaches by which we can evaluate student be-haviour and we can measure the justified course settings. We explored various man-agerial settings inside a concrete course structure. Subsequently there will be statistical evaluation of already cleaned and preprocessed data from the system. At the same time, based on these statistical confirmations, we can propose a set of methodologi-cal recommendations for the teacher, which will help us to improve the quality and effectiveness of the teaching process.

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