VII INTERNATIONAL CONFERENCE
Humanizing Technology:
Ethos of Science Communication in the Era of AI
Humanizing Technology:
Ethos of Science Communication in the Era of AI
November 19-20, 2025
Section under development
Dr. Elena Bazanova specializes in Higher Education pedagogies in TESOL contexts and has a wide range of publications reflecting her teaching and research, including ESP, EAP, and AI-based standardized testing for EAL learners. She received her PhD at Moscow State Linguistic University, where she did research into Internet-assisted language teaching at higher education level. She also holds a Diploma in Educational Management, (UK) and a Harvard Graduate Certificate in Business Rhetoric. She is currently Head of Foreign Languages Department, in addition to being President of the Association of Academic Writing Experts “National Writing Centers Consortium,” which she established in 2017. Elena is especially interested in promoting the global flow of Higher Education innovations in the practice and theory of teaching and learning across all disciplines in higher education.
Elena Bazanova
Ph.D. in TESOL, Associate Professor, President of the Association of Academic Writing Experts “National Writing Centers Consortium”, Director of Academic Writing Office, Russia
Dr. Gerhard Fischer is Professor Emeritus of Computer Science, a Fellow of the Institute of Cognitive Science, and the founder and director for Lifelong Learning and Design (L3D) at the University of Colorado at Boulder. He is a member of the Computer-Human Interaction Academy (CHI; 2007), a Fellow of the Association for Computing Machinery (ACM; 2009), and a recipient of the RIGO Award of ACM-SIGDOC (2012). In 2015, he was awarded an honorary doctorate from the University of Gothenburg, Sweden.
His research has focused on new conceptual frameworks and new media for learning, working, collaborating, human-centered computing, and design. His recent work is centered on quality of life in the digital age, social creativity, meta-design, cultures of participation, design trade-offs, and rich landscapes for learning.
Publications at: http://l3d.cs.colorado.edu/wordpress/people/home-folders/gerhard-fischers-home-page/gerhard-fischers-papers/
His research has focused on new conceptual frameworks and new media for learning, working, collaborating, human-centered computing, and design. His recent work is centered on quality of life in the digital age, social creativity, meta-design, cultures of participation, design trade-offs, and rich landscapes for learning.
Publications at: http://l3d.cs.colorado.edu/wordpress/people/home-folders/gerhard-fischers-home-page/gerhard-fischers-papers/
Gerhard Fischer
Professor Emeritus of Computer Science, a Fellow of the Institute of Cognitive Science, and the founder and director for Lifelong Learning and Design (L3D) at the University of Colorado at Boulder
Kelly Metz-Matthews
Over a decade of experience designing training programs for post-secondary ESL/EFL/EIL educators with a particular focus on educational leadership development, faculty mentorship, participatory and collaborative pedagogies, and critical intercultural communication. Academic Senate Vice President for a faculty body of 400. Supervision of 35-40 ESL faculty and 10-15 ESL project assistants per semester, including both in person and online faculty. Coordination of a campus-wide faculty mentorship program and multiple publications/conference presentations in the area of faculty mentorship. Experience coordinating, implementing, and leading district and campus-wide faculty professional development and educational leadership programming. Completed coursework in educational leadership, language program management, and teacher assessment, evaluation, and supervision.
Keynote
Workshop
Over a decade of experience designing training programs for post-secondary ESL/EFL/EIL educators with a particular focus on educational leadership development, faculty mentorship, participatory and collaborative pedagogies, and critical intercultural communication. Academic Senate Vice President for a faculty body of 400. Supervision of 35-40 ESL faculty and 10-15 ESL project assistants per semester, including both in person and online faculty. Coordination of a campus-wide faculty mentorship program and multiple publications/conference presentations in the area of faculty mentorship. Experience coordinating, implementing, and leading district and campus-wide faculty professional development and educational leadership programming. Completed coursework in educational leadership, language program management, and teacher assessment, evaluation, and supervision.
Keynote
Workshop
Kelly Metz-Matthews
Ph.D. in Educational Leadership for Innovation and Social Justice, University of San Diego, School of Leadership and Education Sciences
Sarah Warfield
Keynote
Workshop
Keynote
Workshop
Sarah Warfield
Lawrence Berlin
Dr. Lawrence N. Berlin is an experienced international educator, applied linguist, and academic leader with over 25 years of work in English language teaching, curriculum innovation, and teacher development. His collaborations with U.S. Embassies and Fulbright programs have included English Language Specialist projects in Bangladesh (2022), where he led Ministry-level teacher training and professional development workshops in cooperation with national TESOL organizations, and Fulbright Specialist appointments in Colombia—first with Universidad Distrital in Bogotá (2013) supporting curriculum design and graduate instruction in discourse analysis, and later with Universidad de Santander (2018), where he developed an internationalization strategy for multi-campus implementation. He has also directed U.S.– Central American student exchange initiatives through grant-funded partnerships.
Paper Presentation
Teaching with AI: Reimagining, Enhancing, and Extending Praxis in the Language Classroom
This presentation revisits the teacher’s central role in the act of becoming—planning, enacting, and extending learning within an age of intelligent tools. Building on Berlin’s continuum of praxis from the 2000 Application Model and Contextualizing College ESL Classroom Praxis (2005), it introduces a renewed framework for the AI era: Reimagining, Enhancing, and Extending. Aligned with the British Council’s (2024) call to humanize learning through purposeful AI integration, the session illustrates how educators can design, engage, and sustain learning more effectively—while reaffirming teaching as an irreducibly human endeavor.
Dr. Lawrence N. Berlin is an experienced international educator, applied linguist, and academic leader with over 25 years of work in English language teaching, curriculum innovation, and teacher development. His collaborations with U.S. Embassies and Fulbright programs have included English Language Specialist projects in Bangladesh (2022), where he led Ministry-level teacher training and professional development workshops in cooperation with national TESOL organizations, and Fulbright Specialist appointments in Colombia—first with Universidad Distrital in Bogotá (2013) supporting curriculum design and graduate instruction in discourse analysis, and later with Universidad de Santander (2018), where he developed an internationalization strategy for multi-campus implementation. He has also directed U.S.– Central American student exchange initiatives through grant-funded partnerships.
Paper Presentation
Teaching with AI: Reimagining, Enhancing, and Extending Praxis in the Language Classroom
This presentation revisits the teacher’s central role in the act of becoming—planning, enacting, and extending learning within an age of intelligent tools. Building on Berlin’s continuum of praxis from the 2000 Application Model and Contextualizing College ESL Classroom Praxis (2005), it introduces a renewed framework for the AI era: Reimagining, Enhancing, and Extending. Aligned with the British Council’s (2024) call to humanize learning through purposeful AI integration, the session illustrates how educators can design, engage, and sustain learning more effectively—while reaffirming teaching as an irreducibly human endeavor.
Lawrence Berlin
Ph.D. Second Language Acquisition and Teaching,
University of Arizona, Tucson, AZ
Consulting Professor, E.C.centric Educational Consultants, S.A., Medellín (metro area), Colombia
University of Arizona, Tucson, AZ
Consulting Professor, E.C.centric Educational Consultants, S.A., Medellín (metro area), Colombia
Artem Sigaev (Tim) joined ITMO University in 2021, where he teaches General English, English for Specific Purpose (ESP), Academic Writing and Presentation Skills to both undergraduate and graduate students. Artem Sigaev is also a member of the PhD Speaking Club and Discussion Forum development team. He holds a B.A. with honors in Foreign Philology and M.A. in Counseling Psychology. In the beginning of 2024 he and his colleague developed a course for ITMO employees "AI in Education: Effective Lesson Design". In his free time, Artem likes to watch movies and read books, which he usually turns into worksheets for his classes.
Paper Presentation
AI as a Feedback Partner in Student Writing
This presentation explores the use of ChatGPT as a feedback partner in student writing assignments in English courses at the Bachelor’s and Master’s levels. Drawing on classroom practice, I will discuss how AI can provide structured, immediate feedback while raising important ethical and pedagogical questions. The talk highlights strategies for integrating AI into writing pedagogy, ensuring transparency, fostering academic integrity, and preserving a human-centered approach in communication between students, teachers, and emerging technologies.
Paper Presentation
AI as a Feedback Partner in Student Writing
This presentation explores the use of ChatGPT as a feedback partner in student writing assignments in English courses at the Bachelor’s and Master’s levels. Drawing on classroom practice, I will discuss how AI can provide structured, immediate feedback while raising important ethical and pedagogical questions. The talk highlights strategies for integrating AI into writing pedagogy, ensuring transparency, fostering academic integrity, and preserving a human-centered approach in communication between students, teachers, and emerging technologies.
Artem Sigaev
B.A. with honors in Foreign Philology, M.A. in Counselling Psychology English Language Specialist, ITMO University, Russia
Elena Trufanova
Paper Presentation
Artificial Intelligent Assistants in the Context of the Concept of "Expanded Mind"
Paper Presentation
Artificial Intelligent Assistants in the Context of the Concept of "Expanded Mind"
Elena Trufanova
D.Sc. (Philosophy), Associate Professor in the Department of the Institute of Philosophy of the Russian Academy of Sciences
Olga Ulyanina graduated in 2004 from Volgograd State Pedagogical University with a degree in Psychology, and in 2014 from Volgograd State University with a degree in Jurisprudence. In 2009, defended a Candidate’s dissertation entitled "Advertising as a Factor in the Formation of Value Orientations of Russian Student Youth: A Case Study of University Students in Volgograd"; in 2019, defended a Doctoral dissertation titled "Psychological Support for the Development of Personal Competence of Internal Affairs Officers in Educational Institutions of the Ministry of Internal Affairs of Russia." From 2014 to 2016, served as Deputy Head of the Department for Moral and Psychological Support, Head of the Psychological Support Division, and Head of the Psychological Service at the Volgograd Academy of the Ministry of Internal Affairs of Russia. Since 2016, she has worked at the Academy of Management of the Ministry of Internal Affairs of Russia: Associate Professor of the Department of Psychology, Pedagogy and Human Resources Management (2016-2019), Leading researcher at the Department for Research on Sectoral Management Problems at the Research Center (2019-2020), Deputy Head of the Department of Psychology, Pedagogy and Human Resources Management, member of the Dissertation Council at the Moscow State University of Psychology and Education (MGPPU) and Academy of Management of the Ministry of Internal Affairs of Russia (2020), Chief Researcher. From 2020 to 2021, Head of the Federal Resource Center of Psychological Services in the Education System of the Russian Academy of Education; teaches at the National Research University Higher School of Economics (HSE). Since 2021, Head of the Federal Coordination Center for the Development of Psychological and Pedagogical Support in the Education System of the Russian Federation, Professor in the Department of Psychology, Faculty of Social Sciences, HSE. Elected Corresponding Member of the Russian Academy of Education in 2021. Since 2025, Chief Researcher at the Center for Applied Linguistic Research and Testing “ISTOK”, Moscow Institute of Physics and Technology (National Research University) (MIPT).
Paper Presentation
The human factor in the age of AI: how the lecture format (face-to-face, Online, with an AI Avatar) affects engagement, psychological climate and understanding of the material
The report is based on an empirical study by MIPT (N=106) and a systematic review on the use of AI in higher education. Three lecture formats are compared: face–to-face, online, and with an AI avatar in terms of engagement, comfort, ease of perception, understanding, and psychological climate. It is shown that the face-to-face format retains the greatest socio-emotional effect; online occupies an intermediate position; the avatar is still inferior mainly in terms of "social presence", with comparable content transmission. Practical recommendations are discussed: the design of emotionally "warm" avatars, enhancing the effect of social presence, and hybrid models.
Paper Presentation
The human factor in the age of AI: how the lecture format (face-to-face, Online, with an AI Avatar) affects engagement, psychological climate and understanding of the material
The report is based on an empirical study by MIPT (N=106) and a systematic review on the use of AI in higher education. Three lecture formats are compared: face–to-face, online, and with an AI avatar in terms of engagement, comfort, ease of perception, understanding, and psychological climate. It is shown that the face-to-face format retains the greatest socio-emotional effect; online occupies an intermediate position; the avatar is still inferior mainly in terms of "social presence", with comparable content transmission. Practical recommendations are discussed: the design of emotionally "warm" avatars, enhancing the effect of social presence, and hybrid models.
Ольга Ульянина
D. Sc. (Psychological Sciences), Corresponding Member of the Russian Academy of Education
Аndrei Alekseev is an engineer-mathematician (1987, Faculty of Automated Control Systems, Leningrad Higher Military School of Communications named after Lensovet), teacher of philosophy (1999, with honors, Faculty of Philosophy, Moscow State University). Since 2005, organizer and academic secretary of the Scientific Council of the Russian Academy of Sciences on the Methodology of Artificial Intelligence and Cognitive Research (2005–2019, at the Department of Social Sciences, Russian Academy of Sciences; from 2019 to the present, at the Presidium of the Russian Academy of Sciences). Her PhD dissertation (2004) was devoted to computer modeling of meaning. Her doctoral dissertation (2016, Faculty of Philosophy, Moscow State University): "Philosophy of Artificial Intelligence: The Conceptual Status of the Сomprehensive Turing Test."
Paper Presentation
The Сomprehensive Turing Test versus the comprehensive digitalization of education
The report is dedicated to the 75th anniversary of artificial intelligence research and the 25th anniversary of the comprehensive Turing test. The Turing test is a conceptual toolkit for computer simulation of a very wide range of cognitive phenomena. It is based on the systematization, formalization, operationalization, and functionalization of elements of the discussions of the original Turing test on the question: "Can a digital machine think?" (1950); specific Turing tests (there are more than a hundred of them) on the questions: "Can a computer understand, live, create, make friends, love, be aware, be an individual, a society, possess subjectivity, convictions, freedom, rights, etc.?" (1950 - present); the comprehensive Turing test (since 2000): "Can a computer do EVERYTHING?", i.e., everything that is specified by specific tests. The comprehensive test clearly reveals both the beneficial and harmful aspects of the digitalization of education as a cognitive sphere of public life. For example, the harmful aspect is that the complex imitation of education fundamentally hinders the strengthening of creative competencies in both students and teachers; the real educational process is replaced by formal reporting (the Unified State Exam, the Federal Advanced Professional Educational Institution); the very idea of artificial intelligence is distorted by so-called "machine learning" of so-called "neural networks"; human teachers and human students are replaced by digital twins, etc. In general, rhetorical figures like the oxymoron "artificial intelligence" cannot serve as the goals of broad socio-humanitarian projects. The meaning of the term "digitalization" of education, as demonstrated by the results of the comprehensive Turing testing, is functionally invariant to the terms "informatization," "computerization," "automation," "cybernetization," etc. There is no pedagogical innovation, but many essential parameters are leveled out.
Paper Presentation
The Сomprehensive Turing Test versus the comprehensive digitalization of education
The report is dedicated to the 75th anniversary of artificial intelligence research and the 25th anniversary of the comprehensive Turing test. The Turing test is a conceptual toolkit for computer simulation of a very wide range of cognitive phenomena. It is based on the systematization, formalization, operationalization, and functionalization of elements of the discussions of the original Turing test on the question: "Can a digital machine think?" (1950); specific Turing tests (there are more than a hundred of them) on the questions: "Can a computer understand, live, create, make friends, love, be aware, be an individual, a society, possess subjectivity, convictions, freedom, rights, etc.?" (1950 - present); the comprehensive Turing test (since 2000): "Can a computer do EVERYTHING?", i.e., everything that is specified by specific tests. The comprehensive test clearly reveals both the beneficial and harmful aspects of the digitalization of education as a cognitive sphere of public life. For example, the harmful aspect is that the complex imitation of education fundamentally hinders the strengthening of creative competencies in both students and teachers; the real educational process is replaced by formal reporting (the Unified State Exam, the Federal Advanced Professional Educational Institution); the very idea of artificial intelligence is distorted by so-called "machine learning" of so-called "neural networks"; human teachers and human students are replaced by digital twins, etc. In general, rhetorical figures like the oxymoron "artificial intelligence" cannot serve as the goals of broad socio-humanitarian projects. The meaning of the term "digitalization" of education, as demonstrated by the results of the comprehensive Turing testing, is functionally invariant to the terms "informatization," "computerization," "automation," "cybernetization," etc. There is no pedagogical innovation, but many essential parameters are leveled out.
Andrei Alekseev
D.Sc. (Philosophy), Peoples' Friendship University of Russia (Engineering Academy), State University of Humanities (Faculty of Philosophy)
Inga Zashikhina, PhD, is an Associate Professor at Northern (Arctic) Federal University, Russia. Her academic focus lies at the dynamic crossroads of philosophy, science, and English as a lingua franca. In her role as Coordinator of the Interdisciplinary Academic Communication Centre, she champions and organizes a wide range of interdisciplinary collaborations within the academic community. Professor Zashikhina is also dedicated to enhancing communication skills, teaching English to university staff and students of all levels. Her current research and publications delve into critical areas such as research and academic writing, scientific publishing, and robust research methodology.
Paper Presentation
Ethics and AI in Scientific Writing: A Cosmotechnical Perspective
This report delves into Yuk Hui's influential philosophy on artificial intelligence, equipping participants with a crucial framework for understanding AI's ethical dimensions. Participants will critically analyze the potential pitfalls of universalizing AI models and algorithmic logic, identifying risks to cultural specificity and diverse forms of knowledge. The report aims to foster algorithmic literacy, enabling participants to advocate for AI development that prioritizes cultural sensitivity and responsibly navigates the changing landscape of the AI age. Ultimately, this empowers them to foster ethical AI solutions that respect and safeguard the rich tapestry of global cultures.
Paper Presentation
Ethics and AI in Scientific Writing: A Cosmotechnical Perspective
This report delves into Yuk Hui's influential philosophy on artificial intelligence, equipping participants with a crucial framework for understanding AI's ethical dimensions. Participants will critically analyze the potential pitfalls of universalizing AI models and algorithmic logic, identifying risks to cultural specificity and diverse forms of knowledge. The report aims to foster algorithmic literacy, enabling participants to advocate for AI development that prioritizes cultural sensitivity and responsibly navigates the changing landscape of the AI age. Ultimately, this empowers them to foster ethical AI solutions that respect and safeguard the rich tapestry of global cultures.
Inga Zashikhina
Ass. Prof., PhD (Philosophy), Dept. of Philosophy and Sociology, Higher School of Social Sciences, Humanities and International Communication, Northern (Arctic) Federal University named after M.V. Lomonosov
Olesya Shadrina is a Senior Lecturer in the Department of Foreign Languages at the Moscow Institute of Physics and Technology (MIPT), Russia. She has 15 years’ experience in higher education and teaches Business English for undergraduate students and English for Advanced Combinatorics on the Master’s programme. She completed postgraduate studies at Tula State Pedagogical University and is currently completing a dissertation on AI terminology. Her research interests lie in corpus linguistics and terminology studies, with recent publications focusing on semantic processes in term formation.
Paper Presentation
Ethical Norms for the Use of Generative Models in Academic Work by University Students and Faculty
Universities increasingly integrate generative AI into teaching and research, raising legal, integrity, and pedagogical questions. This article develops an actionable model for ethical use in higher education, synthesizing scholarship on academic ethics with close readings of user agreements from OpenAI (ChatGPT/DALL·E), Google Gemini, Microsoft Copilot, Anthropic Claude, and Meta Llama. The analysis addresses law (ownership, non-exclusivity, licensing, data governance, privacy), integrity (plagiarism, authorship, mandatory disclosure/attribution), and practice (course and lab policies, assessment design). The model provides criteria for permissible use, a policy rubric (prohibited/conditional/encouraged), and assignment designs that integrate AI through critique, annotation, and prompt logging.
Paper Presentation
Ethical Norms for the Use of Generative Models in Academic Work by University Students and Faculty
Universities increasingly integrate generative AI into teaching and research, raising legal, integrity, and pedagogical questions. This article develops an actionable model for ethical use in higher education, synthesizing scholarship on academic ethics with close readings of user agreements from OpenAI (ChatGPT/DALL·E), Google Gemini, Microsoft Copilot, Anthropic Claude, and Meta Llama. The analysis addresses law (ownership, non-exclusivity, licensing, data governance, privacy), integrity (plagiarism, authorship, mandatory disclosure/attribution), and practice (course and lab policies, assessment design). The model provides criteria for permissible use, a policy rubric (prohibited/conditional/encouraged), and assignment designs that integrate AI through critique, annotation, and prompt logging.
Оlesya Shadrina
Senior lecturer, Moscow Institute of Physics and Technology (MIPT), Russia
Ekaterina Artamonova teaches Spanish language courses for undergraduates at various levels, integrating modern teaching methods, including artificial intelligence. She is the founder of the "Conversation Club" (Habla Club), where students have the opportunity to develop and refine their oral communication skills in an interactive format. Her professional interests include studying the cultural traditions of Spanish-speaking countries, including translating documents on the history of Spanish theater during the Golden Age. Ekaterina Artamonova publishes research articles and participates in scientific conferences.
Paper Presentation
"Philodemus, Shakespeare, Lope de Vega... New possibilities and discoveries in the era of Artificial Intelligence"
Modern Artificial Intelligence (AI) technologies are opening new horizons in the study of the literary legacy of such great authors as Philodemus, Shakespeare, and Lope de Vega. Using computer analysis and machine learning, researchers are successfully identifying the authorship of the texts and uncovering previously unknown works. An interdisciplinary approach, integrating philology, computer science, and history, facilitates a deep understanding of cultural context and expands the capabilities of traditional humanities. This report explores the prospects and results of applying artificial intelligence to literary attribution.
Paper Presentation
"Philodemus, Shakespeare, Lope de Vega... New possibilities and discoveries in the era of Artificial Intelligence"
Modern Artificial Intelligence (AI) technologies are opening new horizons in the study of the literary legacy of such great authors as Philodemus, Shakespeare, and Lope de Vega. Using computer analysis and machine learning, researchers are successfully identifying the authorship of the texts and uncovering previously unknown works. An interdisciplinary approach, integrating philology, computer science, and history, facilitates a deep understanding of cultural context and expands the capabilities of traditional humanities. This report explores the prospects and results of applying artificial intelligence to literary attribution.
Ekaterina Artamonova
PhD, Associate Professor, Moscow Institute of Physics and Technology (MIPT), Russia
Natalia Savina teaches English language courses for for undergraduates at various levels, integrating modern teaching methods, including cognitive-discursive technology and artificial intelligence. Her professional interests include researching new teaching methods, adaptation and integration of new teaching materials. Natalia Savvina publishes research articles and participates actively in scientific conferences.
Paper Presentation
"Philodemus, Shakespeare, Lope de Vega... New possibilities and discoveries in the era of Artificial Intelligence"
Modern Artificial Intelligence (AI) technologies are opening new horizons in the study of the literary legacy of such great authors as Philodemus, Shakespeare, and Lope de Vega. Using computer analysis and machine learning, researchers are successfully identifying the authorship of the texts and uncovering previously unknown works. An interdisciplinary approach, integrating philology, computer science, and history, facilitates a deep understanding of cultural context and expands the capabilities of traditional humanities. This report explores the prospects and results of applying artificial intelligence to literary attribution.
Paper Presentation
"Philodemus, Shakespeare, Lope de Vega... New possibilities and discoveries in the era of Artificial Intelligence"
Modern Artificial Intelligence (AI) technologies are opening new horizons in the study of the literary legacy of such great authors as Philodemus, Shakespeare, and Lope de Vega. Using computer analysis and machine learning, researchers are successfully identifying the authorship of the texts and uncovering previously unknown works. An interdisciplinary approach, integrating philology, computer science, and history, facilitates a deep understanding of cultural context and expands the capabilities of traditional humanities. This report explores the prospects and results of applying artificial intelligence to literary attribution.
Natalia Savina
Senior lecturer, Moscow Institute of Physics and Technology (MIPT), Russia
Dr. Samira Moussaoui is a dedicated educator with a Ph.D. in English Language Teaching and Educational Psychology. She has a strong background in teaching EAP, ESP, research skills, academic writing, and other academic disciplines. Her research interests include, but are not limited to second/foreign language acquisition, academic writing, affect in learning, assessment/feedback, and educational technology.
Paper Presentation
Paper Presentation
Investigating the Impact of Language Variation on Cognitive and Metacognitive Strategies while Brainstorming with ChatGPT
This study investigated the impact of language variation on students’ cognitive and metacognitive strategies while brainstorming with ChatGPT. Paired sample t-test indicates a significant difference between essay scores written using Arabic (L1) vs. English (L2) brainstormed ideas. Students wrote better essays when they interacted with ChatGPT using English. Additionally, each essay was analyzed in parallel with its related ChatGPT conversation log to see how the students transferred ideas into their essays. Students tended to copy English brainstorming more than Arabic ideas, but they improved Arabic brainstormed ideas more often. No significant differences were found for inspiration and conceptual combination.
Samira Moussaoui
Ph.D., member, Dept. Curriculum Committee & Central Research Committee, Centre for Preparatory Studies, Sultan Qaboos University, Oman
Victoria Tevs is a language instructor at the Moscow Institute of Physics and Technology, where she teaches General English and English for Research to undergraduate students. She holds an MA with honors in Philology and is currently a PhD student at Demidov Yaroslavl State University.
Paper Presentation
Paper Presentation
“Digital Aristotle”: A Case Study in Using AI Tools to Design an Educational Game
What if Aristotle had ChatGPT? With AI stepping onto the academic stage, educators can venture beyond the familiar curriculum and explore the territory of creating new materials from scratch. This presentation sheds light on a case study in which AI tools acted as an ally in designing a board game to teach rhetorical principles. Drawing on the hands-on experience, I will argue for a model of AI as a powerful, yet problematic, co-pilot and share practical ideas for educators looking to embark on similar teaching projects.
Victoria Tevs
Lecturer, Moscow Institute of Physics and Technology (MIPT), Russia
Anna Mokrousova graduated with honors from Lomonosov Moscow State University in 2024 with a degree in Translation and Interpretation and received a certificate as a simultaneous interpreter in the English-Russian and French-Russian language pairs. Completed an outreach placement at the United Nations Office in Vienna. Since 2024 I have been teaching English at the Department of Foreign Languages in the Professional Sphere at St. Petersburg State University of Industrial Technologies and Design, and working at the university admission department. Since 2025 I have been doing my postgraduate studies in System Analysis, Management, and Information Processing, Statistics.
Доклад
AI-Supported Statistical Methods for Evidence-Based Placement Test Analysis
This study investigates the integration of artificial intelligence into English as a Foreign Language (EFL) instruction by identifying statistical methods that can be effectively used by instructors without advanced statistical training to analyze placement test results. The research addresses two primary questions: (1) which statistical methods are most effective for interpreting placement test data, and (2) which methods are accessible to instructors depending on their statistical expertise. The study aims to enhance evidence-based pedagogical decision-making and explore the potential of AI tools to humanize and support teaching practices.
Доклад
AI-Supported Statistical Methods for Evidence-Based Placement Test Analysis
This study investigates the integration of artificial intelligence into English as a Foreign Language (EFL) instruction by identifying statistical methods that can be effectively used by instructors without advanced statistical training to analyze placement test results. The research addresses two primary questions: (1) which statistical methods are most effective for interpreting placement test data, and (2) which methods are accessible to instructors depending on their statistical expertise. The study aims to enhance evidence-based pedagogical decision-making and explore the potential of AI tools to humanize and support teaching practices.
Anna Mokrousova
Postgraduate student at the Department of Mathematics. Assistant at the Department of Foreign Languages in the Professional Sphere, Saint Petersburg State University of Industrial Technologies and Design
Dmitriy Tulyakov has numerous publications in applied and corpus linguistics, English for academic purposes, and business communication. He has extensive experience teaching Academic Writing to ESL students and is especially interested in modern approaches to teaching and researching undergraduate and professional writing.
Paper Presentation
Paper Presentation
Inflated by AI: Importance Markers in Human Written and AI-generated Research Abstracts
Generative AI has begun to reshape academic writing, influencing how research is presented. This study examines how AI-generated research abstracts differ from human-written ones in expressing importance. Comparing over 200 authentic abstracts with AI-generated versions of the same texts, we found that while both used similar numbers of importance-related nouns and verbs, AI abstracts contained far more adjectives and adverbs emphasizing significance. These findings suggest that AI not only mirrors but amplifies the promotional tone typical of research writing. Writers should be cautious, as AI tools may inflate the perceived importance of research when summarizing content.
Dmitriy Tulyakov
Cand. Sc. (Philology), Associate Professor, Department of Foreign Languages, HSE University (Perm)