The rapid advancement of Generative AI in academia has raised ethical concerns about academic integrity, particularly in higher education. This study aims to delineate the key ethical concerns prevalent in academia and propose a theoretical framework that incorporates the moral philosophies of deontological ethics for learners and teleological ethics for evaluators. Employing a qualitative methodology and thematic analysis, this research utilized a systematic scoping review of scholarly existing literature. The authors searched eight academic databases, following specific inclusion and exclusion criteria, which resulted in a final set of 71 relevant studies out of 215 for review. The authors found evidence of a lack of academic integrity in higher education, particularly in students’ written assignments. To address this issue the academic literature suggests, the establishment of ethical guidelines have been effective for learners' ethical awareness in using AI. The use of ethical guidelines has also promoted educators to assess learners’ academic written work, emphasizing learners’ own creativity. As generative AI tools become increasingly prevalent, the risk of academic misconduct may escalate, therefore threatening educational institutions' credibility and the integrity of students’ academic qualifications. This study will help students, faculty, and administrators understand how ethical frameworks can mitigate the risk of academic misconduct and foster a culture of ethical awareness among students and educators.

Keywords: Generative AI, Academic Misconduct, Deontological and Teleological Ethical Frames, Ethical Awareness, Ethical Academic Practice, Tertiary Education.