Big Data technology and its influence on the personal well-being of students: psychological risks and legal solutions

Context and relevance. The application of Big Data in university education opens wide opportunities for personalizing learning but is accompanied by psychological risks: impaired perception of autonomy, erosion of trust in the university, increased anxiety, emotional alienation, and reduced student psychological well-being. Mitigating these risks is possible through the integration of psychological and legal aspects, which would ensure a balance between innovation, data protection, and psychological comfort. Objective. To identify the psychological consequences of Big Data application in higher education (HE) and propose solutions that minimize risks and ensure student psychological well-being. Methods. An interdisciplinary approach: student surveys (Likert scale — anxiety, perception of monitoring); interviews (alienation, trust); content analysis; analysis of Federal Law No. 152-FZ (On Personal Data); synthesis of successful practice experience; comparative analysis; triangulation. Results. Established psychological risks include: dehumanization (62% of respondents feel like "data objects"), emotional alienation, loss of autonomy (67% of respondents), anxiety (3.5 on the Likert scale). Successful practices (informed consent, psycho-ethical codes) reduce anxiety (to 2.1) and strengthen trust (+70%). Addressing legal gaps reduces psychological risks and enhances student psychological well-being. Conclusions. Psychological risks associated with Big Data use can be mitigated through transparency in data analytics processes, implementation of psycho-ethical codes, and mandatory faculty involvement in data interpretation. Harmonizing legislation with international standards and conducting regular algorithm audits are necessary to compensate for student feelings of insecurity and anxiety, enhance trust in data analytics, and thereby promote student psychological well-being.

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