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Student Attitudes Toward Declaring Generative AI Use in Academic Writing in Nigerian Library Schools: A Cross-Sectional Survey

Jul 2026 · Education for Information · 0 citations · 31 references

TL;DR

While GenAI tools are deeply integrated into students’ academic writing practices, transparency in their use remains limited due to ambiguity, fear, and insufficient institutional guidance, the study recommends that universities develop clear AI policies, integrate disclosure requirements into assessment practices, and provide structured training to promote ethical and transparent AI use.

Abstract

This study examines students’ attitudes toward declaring the use of generative artificial intelligence (GenAI) in academic writing within Nigerian library schools, against the backdrop of increasing adoption of AI tools and growing concerns about academic integrity and transparency. A cross-sectional survey design was adopted, and data were collected through a structured questionnaire administered to 374 library and information science students across selected Nigerian universities. Descriptive and inferential statistics were used for data analysis. The findings reveal widespread use of AI-assisted academic tools, particularly conversational AI systems, for various academic writing tasks. However, students exhibited generally weak attitudes toward declaring AI use and demonstrated low and inconsistent levels of disclosure, often declaring only when explicitly required. Awareness of institutional policies was also limited, and no significant relationship was found between policy awareness and attitudes toward declaration. The study revealed that the major factors influencing disclosure included fear of academic penalties, lecturer expectations, unclear guidelines, and concerns about negative judgement. The study concludes that while GenAI tools are deeply integrated into students’ academic writing practices, transparency in their use remains limited due to ambiguity, fear, and insufficient institutional guidance. It recommends that universities develop clear AI policies, integrate disclosure requirements into assessment practices, and provide structured training to promote ethical and transparent AI use.

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