The Global Research Landscape of AI and Academic Integrity: A Bibliometric Analysis
DOI:
https://doi.org/10.59175/pijed.v4i2.781Keywords:
Academic Integrity, Artificial Intelligence, Bibliometric Analysis, Machine Learning, Thesis WritingAbstract
The growing application of artificial intelligence (AI), especially technologies based on machine learning, has changed how academics write in higher education and raised issues with academic honesty. This study looks at current research trends on the application of AI to thesis writing worldwide and the ways in which scholarly literature addresses academic integrity. A systematic literature review and bibliometric analysis were performed following the PRISMA framework. The Scopus database was used to gather data using with the keywords “machine learning” and “academic integrity.” A total of 52 peer-reviewed journal articles published between 2016 and September 2025 were examined to determine publication trends, key research themes, and the distribution of scholarly contributions across countries and institutions. The results show that since 2022, publications have significantly increased, demonstrating the increasing scholarly focus on ethical concerns in AI-assisted thesis writing. Themes that predominate include plagiarism detection, authorship and originality, ethical AI use, and pedagogical strategies to preserve academic integrity. The study highlights the necessity of institutional regulations and explicit ethical standards to promote ethical and long-term AI integration in higher education.
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