The Faculty of Humanities was created on December 1, 2014. It trains instructors and researchers in the field of language and literature, as well as specialists in philosophy, history, and modern culture.
The main goal of the faculty is to teach students how to understand and analyse various cultural processes, employ current research strategies, and effectively put their knowledge into practice.
The faculty’s staff are leading Russian academics and practitioners from various cultural fields, as well as invited foreign specialists. Students receive a modern education in the humanities, as well as thorough language preparation, which allows them to find extensive professional opportunities upon graduation. Students are given the opportunity to conduct research and gain practical experience at major private and public establishments.
Our strengths:
1. Interdisciplinary approach
We study the humanities alongside other academic fields so that students can apply their skills in various areas.
2. International cooperation
We maintain active international ties, which allows students to undertake internships and study abroad, as well as broaden their outlook and cultural experiences.
3. Research
We encourage and support student participation in research projects. This gives them an opportunity to apply their knowledge in practice and make a contribution to the development of the humanities.
Our graduates pursue careers in public and commercial organisations and various types of mass media. They also implement their own media, cultural, social, and educational projects.
Publications
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Book
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Article
Prompt Design for GPT-4 Assessments of EFL Student Reports
This study investigates the impact of different prompt design strategies on the performance of GPT-4 in
assessing undergraduate reports within an English as a Foreign Language (EFL) context. As Large
Language Models (LLMs) increasingly integrate into educational assessment, understanding how
prompt engineering affects grading accuracy and alignment with human judgment is crucial. Three
prompt design methods—TELeR Taxonomy, Six strategies framework, and Zero-shot prompting—
were applied to evaluate 40 student business reports. The assessments were compared against human
teacher scores using quantitative statistical analysis, specifically box-and-whisker plots and inter-rater
agreement between teacher ratings and AI-generated scores using Cohen’s κ and quadratic weighted κ.
Findings indicate that the choice of prompt design significantly influences the alignment between AI
and human grading. The Six strategies method demonstrated strong alignment with teacher assessments,
particularly in evaluating coherence and cohesion. The Zero-shot prompt demonstrated the strongest
alignment with teacher ratings, yielding the most similar score distribution and the highest inter-rater
agreement (quadratic weighted κ = 0.65). The results suggest that although this strategy most effectively
approximates human scoring in AI-assisted assessment, human oversight remains essential for capturing
the subjective and nuanced aspects of student writing.Journal of Asia TEFL. 2026. Vol. 23. No. 2. P. 490-505.
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Book chapter
Little Lies for Positive Communication: Pitfalls of Interaction at the Crossroads of Cultures
The paper dwells upon the phenomenon of positive communication as
a way of constructing alternative social reality; it is also explored cross- culturally
in interaction with culturally dissimilar Others. Positive communication is contrasted
with negative communication. In this perspective, positive communication
is considered as a social- interactional phenomenon of a pragmatic nature. Cultural
diff erences in conceptualizing positive communication viewed as pitfalls of
intercultural interaction are examined. Little lies are focused upon and analyzed
as a pragmatic value, a cultural norm, and ‘a new normal’ aimed at creating
positivity in relations with communicative partners. An attempt is being made to
identify typical motives for using little lies in communication by means of a survey
among Russian and international students primarily from South Asian cultures.
Other methods used in the ongoing research are participant and non-participant
observation, social and mental experiment as well as case studies, followed by
duoethnographic interpretation of the results.In bk.: Proceedings of the International Science Conference “APPLIED RESEARCH. GLOBAL SOLUTIONS” (May 6, 2026). Istanbul. Turkey. Part 2.. Scientific publishing house Infinity, 2026. P. 158-166.
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Working paper
An Annotation Scheme and Classifier for Personal Facts in Dialogue
The advancement of Large Language Models (LLMs) has enabled their application in personalized dialogue systems. We present an extended annotation scheme for personal fact classification that addresses limitations in existing approaches, particularly PeaCoK. Our scheme introduces new categories (Demographics, Possessions) and attributes (Duration, Validity, Followup) that enable structured storage, quality filtering, and identification of facts suitable for dialogue continuation. We manually annotated 2,779 facts from Multi-Session Chat and trained a multi-head classifier based on transformer encoders. Combined with the Gemma-300M encoder, the classifier achieves 81.6±2.6\% macro F1, outperforming all few-shot LLM baselines (best: GPT-5.4-mini, 72.92\%) by nearly 9 percentage points while requiring substantially fewer computational resources. Error analysis reveals persistent challenges in semantic boundary disambiguation, temporal aspect interpretation, and pragmatic reasoning for followup assessment. The dataset\footnotemark[1] and classifier\footnotemark[2] are publicly available.arxiv.org. Computer Science. Cornell University, 2026