Designing a Personalized Learning Environment in Digital Humanities: AI Competencies, Interdisciplinarity, and Ethical Aspects

In the contemporary educational paradigm, learning is viewed as an integration of scientific knowledge, technological innovation, and pedagogical strategies. The process of transforming academic knowledge into digital educational content requires a profound interpretation of the subject area through the application of appropriate methodological approaches. This article explores the experience of training specialists in the field of Digital Humanities during the transition from e-learning systems to a personalized learning environment. The authors substantiate the systemic nature of this transformation by identifying four interconnected components within the learning structure: target, diagnostic, methodological, and technological. Key aspects of the study include: Competency framework: based on the target component, the authors have developed a competency system that defines the proficiency level of graduates in AI technologies. Ethics and AI: the article examines ethical considerations and the specific applications of AI in professional activities. Interdisciplinary collaboration: the study analyzes a unique "University–Museum" partnership (exemplified by the long-standing collaboration between St. Petersburg State University and the State Russian Museum) and explores the scalability of this model within the international educational space emphase vital significance of the State Russian Museum’s multimedia archives as a one of key factors of international cooperation in education. Methodological evolution: The transformation of the traditional project-based method into a hackathon format is described as a means to foster student autonomy and the development of learner agency. The authors emphasize the following key factors of creating personalized educational trajectories for students: digital heritage, international and interdisciplinary cooperation. The article concludes by highlighting the principle of human-centricity, which must remain a priority when integrating AI solutions into the educational process, ensuring a balance between technological progress and professional ethics.