Abstract:

The relevance of a problem is determined by the need to implement scientifically based pedagogical management based on pedagogical monitoring data. Currently, due to the digitalization of education, a large amount of heterogeneous data of pedagogical monitoring is accumulating: quantitative data of teaching indicators and qualitative psychological indicators of students personalities . The article presents the author's algorithms for the preparation of heterogeneous data of pedagogical monitoring for subsequent automated processing. The described technologies allow the use of accumulated data arrays to build predictive models in education. The proposed technology may be applicable for processing and visualization of a large number of indicators during as traditional education as the mass on-line courses. The materials of the article can be useful to undergraduates, teachers of higher educational institutions, graduate students and everyone interested in the use of data mining in education.