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INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES INTO PROFESSIONAL LANGUAGE TRAINING FOR LAW STUDENTS

2026·0 Zitationen·Європейський правничий часопис.Open Access
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2026

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Abstract

The proliferation of artificial intelligence (AI) in legal practice has fundamentally altered the communicative competencies required of law graduates, necessitating a corresponding change of professional language instruction in higher education. This article investigates the integration of AI technologies into English for Specific Purposes (ESP) curricula for law students, with particular reference to the four speech activity types: reading, writing, listening, and speaking. Employing the methodology that combines qualitative documentary analysis, comparative legal-educational examination, and deductive framework construction, the study analyses twelve Ukrainian and international scholarly sources published between 2023 and 2025. The comparative analysis reveals that international research employs large-sample quantitative methods to capture broader proficiency outcomes, whereas Ukrainian scholarship characteristically foregrounds competency standards, institutional policy, and copyright issues specific to the national higher education context. Both research traditions document measurable gains in legal vocabulary acquisition and written production whilst sharing a critical gap: the absence of a pedagogically principled instructional model that systematically maps AI tool deployment onto all four speech activity types. To address this lacuna, the article proposes an evidencebased integration framework that assigns specific AI tools – including ChatGPT, Grammarly, DeepL, and speech-recognition platforms – to targeted instructional activities across six stages of progressively reduced scaffolding and expanded learner autonomy. The framework is underpinned by three governing principles: purposeful pedagogical alignment, critical mediation of AI-generated output, and graduated independence in professional language production. The article argues that effective AI integration must be grounded in competency-oriented pedagogical design, institutional policy frameworks, and a principled approach to academic integrity

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