Human-AI Academic Writing, Integrity, and Language-Communicative Culture in Teacher Education: Evidence from Ukrainian Student Texts

Are we reading the researchers or the artificial intelligence? Transformations in academic writing after the expansion of generative AI

The rapid expansion of generative artificial intelligence (AI) has intensified debates on authorship and authenticity in academic discourse, yet empirical evidence remains limited. This ex post facto study examines how AI has transformed textual quality in education research. A corpus of 1,000 open access articles indexed in Google Scholar was analysed, comparing papers published up to 2021 (pre-AI) with those from 2024 onwards (AI era). Textual quality was assessed using a validated 25‑item instrument covering five dimensions: orthographic and grammatical accuracy, cohesion and coherence, adequacy to academic register, style and readability, and formal conventions. Results reveal significant differences. Pre‑2021 articles scored higher in accuracy, cohesion, register adequacy, and formal conventions, while post‑2024 articles excelled in style and readability. Findings indicate a discursive shift: AI enhances accessibility and fluency but may compromise rigour and authorial distinctiveness. These results highlight the need to reassess academic writing standards in digitalised contexts.

Artificial Intelligence and academic writing in higher education: a comparative analysis of linguistic indicators in student texts

Generative text as a challenge to creativity and academic ethics

Generative artificial intelligence (AI) tools based on large language model (LLM) technology are transforming processes of creation, writing, and learning in higher education, raising questions about authorship, originality, and academic responsibility. Despite the growing body of research, existing studies mainly focus on regulation and plagiarism, while paying less attention to broader transformations in creativity and academic ethics. The aim of this article is to analyse how generative text reshapes the understanding of creative activity and academic ethics in educational and research contexts. The study adopts a qualitative, theoretical-analytical approach combining hermeneutic and discourse analysis. The analysis is based on three illustrative cases from language learning, translation practice, and academic writing, which are examined as analytical instances to explore emerging ethical and cultural tensions. The findings indicate that the key challenges associated with generative AI are primarily cultural and pedagogical rather than technological. Generative systems redistribute creative agency between human actors and algorithmic tools, transforming the role of the author into that of an editor, coordinator, and ethical decision-maker. While AI enhances productivity and linguistic accuracy, unreflective use risks diminishing interpretive depth, personal voice, and value-based reasoning. The results highlight the need to reconceptualise academic integrity as a reflective process-oriented practice and to develop educational frameworks that promote ethical literacy, transparency, and responsible authorship. The study contributes to the field by offering an integrative perspective that positions generative AI as a catalyst for rethinking creativity, authorship, and ethical responsibility in contemporary higher education.

SILENCE IN AI TEXTS: INVESTIGATING THE LOSS OF INTERPERSONAL MEANING IN GENAI-PRODUCED ACADEMIC PASSAGES

It is revealed that GenAI texts underrepresent the subtle interpersonal cues that give writing its persuasive, dialogic, and ethical texture, though they excel in both grammatical accuracy, and lexical variety.

English Literature and Language as a Medium of Artificial Intelligence Instruction at Tertiary Level Classrooms: Indian Teachers' Perspective

This study proposes an empirical investigation into Indian teachers’ perspectives on using English language and English literary texts as a pedagogical medium for introducing and teaching Artificial Intelligence (AI) at the tertiary level. The study is conceptually grounded in the contemporary debate on English as a Medium of Instruction (EMI), but extends that debate from general academic content to AI-related instruction. The starting point is the documented Indian classroom reality that English may be officially preferred while teachers and learners continue to rely on mother tongues, translation and code-switching because of differences in language proficiency, confidence and institutional support. The present study argues that English language can provide the communicative and terminological foundation for AI literacy, while literature can provide narratives, ethical dilemmas, cultural perspectives, interpretation, critical reading and humanistic reflection through which AI can be understood beyond its technical dimensions. A quantitative, cross-sectional survey design is proposed, using a structured questionnaire for teachers from urban, semi-urban and rural higher-education institutions and across disciplinary backgrounds. The instrument is organized around five constructs: perceived linguistic accessibility, literary-pedagogical usefulness, AI teaching readiness, ethical and critical AI awareness, and institutional support. The paper develops research questions, hypotheses, a sampling strategy, an instrument, an analytical framework and a proposed model for interpreting findings. Importantly, no empirical findings are fabricated in this draft; numerical results should be inserted only after actual data collection and statistical analysis. The study is expected to contribute to discussions on English-medium instruction, AI literacy, human-centred pedagogy and the role of English studies in contemporary Indian higher education.

AI Tools and Writing Identity in EFL Contexts: A Mixed-Methods Study of Voice, Ownership, and Cultural Authenticity

Artificial intelligence tools are increasingly integrated into second language writing (L2) classrooms, offering immediate feedback and scaffolding. While their potential to enhance accuracy and fluency is widely acknowledged, concerns remain about how AI mediation affects learners’ voice and identity. This study investigates whether first-year university students perceive a loss of authenticity in their writing when assisted by AI. A mixed-methods explanatory convergent design was employed with twenty first-year Algerian university students enrolled in English writing courses at the Affiliate of Teacher Education College-Tebessa. A structured questionnaire was used to focus on perceptions of voice, identity, and ownership in AI-assisted texts. Quantitative data were analyzed using descriptive statistics, while qualitative responses were coded thematically to capture nuanced reflections on authenticity and cultural expression. Findings indicate that students value AI for reducing anxiety and improving grammatical accuracy, yet many express ambivalence about authorship and personal voice. Patterns suggest selective acceptance of AI feedback, with students often re-editing outputs to reintroduce their preferred style. The study highlights the dual role of AI as both an enabler and a potential suppressor of identity in L2 writing. These findings underscore the need for pedagogical strategies that encourage critical engagement with AI suggestions.