ARPHA Proceedings 3: 625-632, doi: 10.3897/ap.2.e0625
Identification of Key Factors in the Formation of an Individual Trajectory of Teacher Professional Development in Digital Environment Based on Big Data
expand article infoFail M. Gafarov, Anis F. Galimyanov
Open Access
The relevance of the study is determined by the need to build new methods for the study of educational activities. Currently, electronic document management has become a daily occurrence and all documents, including diaries, class journals and annual reports, exist in electronic form. These digital data occupy a very large memory and are constantly updated both in volume and in nomenclature. There are special methods for processing unstructured and partially structured data called big data. With proper processing, this data can be used in the further optimal design of the educational process. In this regard, this article is aimed at revealing the features of the use of big data methods in the educational process, as well as the rationale for the use of machine learning methods and neural networks to study the hidden patterns in educational process. The use of big data and machine learning methods will help determine the key factors in the formation of the individual trajectory of the teacher's professional development in the digital environment.
big data, educational process, educational environment, neural networks, machine learning