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List of publications on a keyword: «artificial intelligence in education»

  • Intelligent Web Services and Semantic Technologies in Digital Educational Resources

    Conference Paper
    Digitalization in the education system: best practices and implementation practices
    Authors:
    Sofiia D. Nikitina, Kristina F. Iliasova, Andrei M. Zhdanov, Kirill A. Koldenkov, Natalia E. Cherniavskaia
    Work direction:
    Цифровые образовательные ресурсы
    Abstract:
    The article explores the principal aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED). The study demonstrates that WI creates new possibilities for personalization of learning, adaptive educational services and semantic integration of learning materials. Special attention is devoted to components such as ontologies, intelligent Web services, semantic markup and Web mining. The architecture of intelligent educational servers INES is proposed, and usage scenarios are described. The authors conclude that the introduction of WI methods into e-learning systems increases adaptability, automation and learner comfort.
    Keywords:
    adaptive learning, ontologies, artificial intelligence in education, Web Intelligence, Semantic Web, pedagogical agents, Web mining, intelligent Web services

  • Artificial intelligence and digital tools in contemporary education: opportunities, challenges and implementation strategies

    Conference Paper
    Advanced Pedagogical Experience in the Modern Educational Space
    Authors:
    Tikhon A. Markin, Nikita A. Lagutin, Inessa S. Kappusheva
    Work direction:
    Цифровые инструменты и искусственный интеллект в образовании
    Abstract:
    This paper examines the current landscape of AI and digital tool integration in educational environments, analysing key application domains and their pedagogical implications. Drawing on empirical research, OECD statistical data, and UNESCO policy guidance, the study identifies the principal areas in which AI is transforming teaching and learning: adaptive learning systems, intelligent tutoring, automated assessment, and administrative automation. Barriers to effective implementation – including infrastructure gaps, teacher readiness, data privacy concerns, and algorithmic bias – are systematically analysed. Strategic recommendations are proposed for educators and policymakers seeking to harness AI capabilities while mitigating associated risks. The findings emphasise that sustainable integration requires a systemic approach that prioritises pedagogical intent over technological novelty.
    Keywords:
    adaptive learning, educational technology, digital transformation, digital tools, artificial intelligence in education, intelligent tutoring systems
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  • Modern technologies in education: classification, effectiveness, and integration strategies

    Conference Paper
    Education, innovation, research as a resource for community development
    Authors:
    Egor D. Tyurin, Ivan A. Rossiyskiy, Nina E. Ioffe
    Work direction:
    Современные технологии в образовании
    Abstract:
    This paper examines modern educational technologies across six functional categories: learning management systems, artificial intelligence tools, virtual and augmented reality, gamification platforms, cloud collaboration tools, and MOOC platforms. Based on empirical research from 2021 to 2025, the study evaluates the effectiveness of each technology type, identifies key implementation challenges, and proposes an evidence-based framework for strategic technology integration.
    Keywords:
    modern educational technologies, artificial intelligence in education
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  • Developing Critical Thinking in Future Foreign Language Teachers Through Generative Language Models: A Systematic Review of Empirical Studies

    Review Article
    Development of education Volume 9 No 1
    Authors:
    Svetlana V. Chusovlianova, Elena G. Zharikova
    Work direction:
    Pedagogy and Modern Education
    Abstract:
    In the context of digital transformation in education, the development of critical thinking among future teachers has become increasingly urgent due to widespread integration of generative artificial intelligence (AI) into teaching and learning processes. This paper presents a systematic review of empirical studies (2019–2025) that examine the pedagogical potential of generative language models for fostering critical thinking among students in teacher education programs. This work constitutes a secondary analysis; it synthesizes findings from ten peer-reviewed empirical and theory-informed empirical studies conducted in Russia, China, Saudi Arabia, and other countries. The literature analysis reveals that effective use of neural network-based AI tools can support the development of core critical thinking operations provided that specific pedagogical strategies are employed. At the same time, the review systematically identifies key risks associated with AI integration: cognitive laziness, academic dishonesty, and the unreliability of generated information. The paper emphasizes the necessity of cultivating students’ digital and critical literacy as a prerequisite for mindful engagement with AI-generated content, as well as the transformation of the teacher’s role from a knowledge transmitter to a facilitator of a reflective-discursive learning environment. This systematic review contributes to the theory of digital pedagogy by proposing an approach to integrating generative AI models into the professional training of language teachers.
    Keywords:
    critical thinking, teacher training, active learning, artificial intelligence in education, future foreign language teachers, reflective learning
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  • The Use of Digital Technologies in Teaching Mathematics: From "Black Box" Systems to Intelligent Pedagogical Environments

    Review Article
    Development of education Volume 9 No 1
    Author:
    Egor V. Malyutin
    Work direction:
    Pedagogy and Modern Education
    Abstract:
    This article is dedicated to analyzing the impact of digital technologies on the process of learning mathematics. Based on the author's proposed four-component typology of digital tools – Black Box systems, Digital Workbooks, Intelligent Tutoring Systems (ITS), and AI-based Systems – their pedagogical effects and associated cognitive risks are examined. It is shown that digital tools effectively develop procedural and algorithmic skills, provide rapid feedback, and support individualized learning. However, their uncontrolled application can lead to the displacement of analytical and creative components of mathematical thinking, the formation of superficial, instrumental motivation, and dependence on automated solutions. Particular attention is paid to the risks associated with AI systems, which, while possessing the potential for dialogic support and analysis of reasoning, can simultaneously foster the passive assimilation of ready-made solutions and diminish student autonomy. The article emphasizes the necessity of thoughtful didactic integration of digital technologies into the educational process, where they serve not as a replacement but as a means of enhancing intellectual activity, thereby ensuring the development of full-fledged mathematical thinking, encompassing the capacity for analysis, reasoning, and creative inquiry.
    Keywords:
    digital technologies, digitalization of education, artificial intelligence in education, mathematics education, intelligent tutoring systems
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  • AI Assistants as Tutors: Ethical Boundaries for Using Neural Networks to Personalize Programming Education

    Conference Paper
    Education, innovation, research as a resource for community development
    Authors:
    Inna G. Iglinskaia, Anastasiia V. Petrakova
    Work direction:
    Использование нестандартных решений для повышения качества, доступности и эффективности образования
    Abstract:
    The article discusses the current problem of integrating artificial intelligence (AI), in particular, large language models (LLM), into the educational process of training specialists in the specialty 02/09/07 "Information Systems and Programming". The purpose of the study is to analyze the potential of AI assistants as personalized tutors to develop programming skills and identify the associated ethical risks and pedagogical limitations. Based on the analysis of modern literature and the author's practical experience, key dilemmas have been identified: the reliability of the generated code and explanations, the risk of intellectual dependence, issues of academic integrity and digital inequality. The article offers a model for the balanced use of AI assistants based on the principles of pedagogical support, the development of critical thinking and the formation of digital hygiene among students. It is concluded that AI is a powerful tool for improving the accessibility and effectivenes
    Keywords:
    pedagogical design, tutoring, ChatGPT, programming, AI ethics, academic integrity, artificial intelligence in education, learning personalization, large language models (LLM), and professional education
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