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IPS146 Motoryn R. et al.
Research on the use of Big Data in the education system is quite
fragmented.
An important aspect of Big Data research is the infrastructure of the data
collected. Therefore, F. A. De Almeida Neto and A. Castro developed a model
where the data created from the interaction between users and the platform
itself is selected, collected and stored in local databases considering the online
platforms that host educational events, [1]. Then local databases are collected
and grouped into a global database.
Some aspects of this research area are issues related to the achievement
of educational results. EDM (Educational Data Mining) is described as a means
of increasing the effectiveness of e-learning. So, M. Nasiri, B. Minai, F. Wafai
considered a model for predicting academic success through monitoring and
supporting first-year students [2].
Other issues of the research are aspects of Big Data related to the
interaction of subjects of education. G. Mobasher, A. Shavish, O. Ibrahim
describe the structure of a large database in education, which contains
demographic data of students, psychological characteristics of students,
lecturers and parents [3]. V. Tem described the approach to the organization
of collaborative learning, allowing to identify educational patterns based on a
diverse set of educational online resources [4]. S. Dwivedi, V. S. K. Roshni, at
the basis of analysts, describe the technology for students to select the most
appropriate elective courses [5].

2. Methodology
The processing of large archives and large data streams requires new
technologies, among which a special place is occupied by Big Data
technologies.
The term Big Data refers to the large and complex data sets, which can be
structured or unstructured, and occupy a very large amount of disk space.
Features Big Data can be described by «5V» rule:
- 1V (volume): the amount of physical data is significant. Large amount of data
mean information about a large number of students and thousands of
educational institutions. These data are accumulating and provide information
that can be used to effectively manage the learning process.
- 2V (velocity): speed data collection and processing speed results фку
relatively high; for example, data on marks for a lesson are entered no later
than the end of the day they are received; the teacher after entering the data
almost immediately can get acquainted with the analytics performance. The
rate of change of big data allows to interactively monitor the learning process
and respond to any changes in the learning process in a timely manner. The
use of interactive tests allows teachers to identify students who give incorrect

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