Learning analytics as a tool for personalization and quality management in the system of professional education of the Federal Penitentiary Service of Russia

This article examines aspects of the application of learning analytics as a promising scientific and applied field aimed at improving the efficiency of the educational process in departmental professional education. The relevance of the study is determined by the need to transition from traditional summative methods of assessing learning outcomes to systematic quality management of specialist training for the Penal System of the Russian Federation, based on the objective analysis of educational data. The integration of digital learning environments (DLEs) into the activities of educational organizations of the Penal System of Russia creates a demand for the development of specialized tools for interpreting students' «digital footprints», enabling the personalization of educational trajectories and the prediction of academic risks. Considerable attention is paid in the work to a comprehensive classification of data sources for learning analytics. The author identifies behavioral data from DLEs, traditional academic indicators, interactive data, biometric parameters, and socio-demographic factors. The value of each data type for constructing a multi-level Departmental Learning Analytics System (DLAS) is substantiated. The architecture of this system provides for the integration of heterogeneous information flows, their analytical modeling, and the practical interpretation of results. A set of regulatory, ethical, and methodological problems hindering its widespread implementation in departmental higher education institutions is outlined. Special emphasis is placed on the need to maintain a balance between the depth of data analysis and ensuring the lawful use of personal information in accordance with Russian legislation. The author formulates principles for the ethical application of analytical tools, including mechanisms for data depersonalization and ensuring informed consent. Based on the conducted analysis, conceptual approaches to building a learning analytics system adapted to the realities of departmental education are proposed. This facilitates a shift from fragmented data collection to proactive quality management of professional training within the Penal System of Russia. Considerable attention is paid to the consideration of the specifics of the use of various types of data sources that can be used when analyzing the behavior of students in the learning process. Along with the enumeration of the undeniable advantages of using educational analytics, the problem of staffing in educational organizations is identified, which prevents its widespread use. The author suggests ways to solve this problem, including through the development and implementation of special programs of additional professional education in the field of data analysis. Based on the review of scientific literature and his own pedagogical experience, the author notes the barriers hindering the widespread introduction of educational analytics tools into the activities of educational organizations, and formulates recommendations on the selection and use of tools when conducting data mining in electronic educational environments.