Methodology of Data-Driven Pedagogy and the Development of a Culture of Analysis of Educational Data in Pedagogical Communities
Author(s) -
Olga А. Fiofanova
Publication year - 2020
Publication title -
arpha proceedings
Language(s) - English
Resource type - Conference proceedings
ISSN - 2683-0183
DOI - 10.3897/ap.2.e0597
Subject(s) - field (mathematics) , educational data mining , big data , reflection (computer programming) , data analysis , subject (documents) , learning analytics , computer science , pedagogy , knowledge management , mathematics education , sociology , engineering ethics , data science , psychology , engineering , world wide web , data mining , mathematics , pure mathematics , programming language
The application of the technology of big data analysis as an end-to-end technology of the National Research Initiative of Russia and its integration in the field of education and education management is being updated. The purpose of the article is to analyze the methodology and methods of analyzing educational data in education and ways of developing a culture of analysis of educational data in pedagogical communities. The study is based on a systematic and methodological approach based on the analysis of educational data (Educational Data Mining), and methods of intellectual analysis of educational data, which allows us to develop the methodology of "Pedagogy based on data." The results of the study: the methodological foundations of pedagogy based on data are characterized as a new field of pedagogical knowledge and practice. The methods of analyzing educational data are systematized depending on the subject of analytics. Pedagogical reflection is considered as the basis for the development of professional competencies of teachers in the analysis of educational data and organizational and pedagogical competencies in managing the quality of educational results of students. The methods of introducing teachers to the culture of the analysis of educational data are analyzed. The developed approaches allow developing the competencies of teachers in the field of analysis of educational data in practice.
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