Navigating Ethical Frameworks to Mitigate Academic Misconduct While Leveraging Generative AI

Abstract The rapid advancement of Generative AI in academia raises ethical concerns about academic integrity. This study aims to delineate the key ethical concerns prevalent in academia and propose a theoretical framework that incorporates deontological ethics for learners and teleological ethics for evaluators. Employing a qualitative methodology and thematic analysis, this research undertakes a systematic scoping review of scholarly articles. The researcher searched various academic databases, following specific inclusion and exclusion criteria, and he selected a final set of 68 relevant studies out of 200 for review. The study found the lack of academic integrity, particularly in written assignments, due to the heightened risk of plagiarism, and to address them, the establishment of ethical guidelines was effective for learners' ethical awareness in using AI and inspiring educators to assess learners’ academic creation emphasizing learners’ own creativity. The study has the potential to inform the development of ethical guidelines for the use of AI in academia. As generative AI tools become increasingly prevalent, the risk of academic misconduct escalates, thereby threatening educational institutions' credibility and academic qualifications' integrity. The study will help to understand how ethical frameworks can mitigate the risk of plagiarism and foster a culture of ethical awareness among students and educators.