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Artificial Intelligence in Education and Academic Integrity in Ukraine

The rapid integration of large language models into educational environments necessitates a re-evaluation of traditional academic integrity standards. This study examines the intersection of technological advancement and ethical oversight, focusing on the development of normative frameworks and institutional practices within the Ukrainian higher education system.

Goal of work

To develop a scientific approach to the integration of artificial intelligence that upholds the principles of academic integrity.

Methodology

Systemic-structural analysis, formal-logical method, and comparative legal review.

Scientific novelty

It proposes a framework for institutional policy-making that prioritizes human-AI collaboration over restrictive bans.

Academic writing sample

This shows the style and logic of the writing, not a final excerpt from the document.

Analysis

Tensions in Academic Authorship

The emergence of generative models challenges the traditional definition of human authorship, creating a dichotomy between efficiency and integrity [3]. While AI offers potential for personalized learning and improved research workflows [4][5], it simultaneously introduces risks of biased reasoning and the dissemination of unverified data [2]. The analysis reveals that the primary challenge for Ukrainian institutions lies in balancing the adoption of these tools with the necessity for human oversight and rigorous citation practices [1][2].

Method

Methodological Approach to Regulatory Analysis

This study employs a formal-logical method to identify manifestations of AI use in scientific activities [2], supplemented by a systemic-structural approach to evaluate institutional compliance [1]. The research corpus includes national policy documents, international legal standards, and comparative pedagogical reports [4][5]. Limitations are addressed by focusing on the qualitative evolution of academic ethics rather than quantitative metrics of AI adoption, ensuring a focus on normative developments [1][6].

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Artificial Intelligence in Education and Academic Integrity in Ukraine

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First M. Last

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Dr. First Last

City, 2026

Introduction

The global proliferation of artificial intelligence (AI) has fundamentally altered the landscape of higher education, necessitating a critical re-examination of academic integrity standards [1][2]. As educational institutions in Ukraine navigate this digital transformation, they face the dual challenge of harnessing AI’s potential for innovation while mitigating risks related to plagiarism and the erosion of critical thinking [4][5].

Existing literature highlights that while AI tools can enhance research efficiency and clinical decision-making, they also introduce significant threats to the reliability of the scientific record [3][5]. The absence of comprehensive national legislation in many regions, including Ukraine, leaves a gap in how institutions define and enforce ethical boundaries regarding AI-generated content [1][2].

This article aims to analyze the current developments in the use of AI within the Ukrainian academic environment and propose a structured approach to maintaining integrity. By employing a comparative legal analysis and systemic evaluation of pedagogical practices, the study seeks to establish a foundation for ethical AI adoption that supports, rather than replaces, human expertise [2][6].

References

  1. Academic Integrity in The Age of Artificial Intelligence: World Trends and Outlook for Ukraine from The Legal Perspective (2024)
    V. Teremetskyi, Y. Burylo, Olha Zozuliak et al.
    Open Source
  2. USE OF ARTIFICIAL INTELLIGENCE AND ACADEMIC INTEGRITY: THE PRIVATE-LAW ASPECT (2025)
    I. Michurin
    Open Source
  3. Artificial Intelligence for Academic Text Generation in Analytical Chemistry: Current Risks, Indicators, and Perspectives toward Greener and More Sustainable Approaches. (2026)
    Adrián Fuente-Ballesteros, Vânia G. Zuin Zeidler
    Open Source
  4. Artificial intelligence in academic writing and clinical pharmacy education: consequences and opportunities (2024)
    A. Weidmann
  5. Artificial Intelligence in Medical Education: Opportunities and Challenges (2025)
    M. Salam, Sakib Imtiaz, I. B. Lucy
  6. Artificial Intelligence and Academic Integrity in Educational Institutions of Ukraine (2023)
    Anastasiia Sokolova

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