Digital Transformation of University Historical Education in the Era of Artificial Intelligence: Scientific and Methodological Conference at Lomonosov Moscow State University

On January 30, 2026, a nationwide conference on the digital transformation of historical education was held at the Faculty of History of Lomonosov Moscow State University, gathering 122 participants (including 57 candidates and 18 doctoral students) from 27 cities in Russia and 6 CIS countries. The main methods and approaches to transforming educational technologies discussed at the conference included the following areas: digital technologies and artificial intelligence in teaching (the use of large language models – LLM, prompt engineering for source analysis, generative text translation using neural networks, the application of ChatGPT for educational and research purposes); analytical data processing methods (network and spatial analysis, use of the Python programming language), as well as technologies for three-dimensional virtual reconstructions of historical and cultural heritage objects. Original developments in the use of digital technologies and artificial intelligence in education were presented by speakers from MSU, Tomsk, Nizhny Novgorod State Universities, Ural Federal University, and RUT MIIT. Data processing methods using the results of scientific projects were demonstrated in a series of reports from the MSU Department of Historical Informatics: R environment, QGIS, 3D reconstructions, VR/AR. The main results presented at the conference showed a great interest among students in neural networks (primarily for their own research interests, for translation from foreign languages, as well as for recognizing handwritten and old printed texts using programs like Transkribus); successful experience in implementing digital platforms and information systems in education ("Single Window of Resources", archival AIS "Great Descriptions" for part-time students, etc.); a noticeable trend in the use of ChatGPT – from information retrieval to source analysis and idea generation; the emergence of a new system for checking academic texts for plagiarism and using generative AI (report by Yu.V. Chekhovich, IPU RAS). Thus, the conference demonstrated a transition from discussing the potential of artificial intelligence to specific methodologies and measurable educational outcomes.