Exploring Ethical Perceptions of AI Use in Academic Integrity Among Students in Teacher Education and Business Studies

The paper investigates ethical perceptions toward the use of AI in terms of academic integrity among students in the teacher education and business programs of ELJ Memorial College, Philippines. Informed by the Ethical Risk Mitigation Framework, the study explores how students in the two departments understand and rank order risks associated with AI, focusing on bias and discrimination, privacy and security, transparency, over-reliance, and equity. The research utilized an exploratory mixed-methods design, combining a descriptive cross-sectional survey with qualitative data collection via interviews. Quantitative data were analyzed using descriptive statistics (mean, median, and IQR) and Mann-Whitney U, while qualitative data were thematically analyzed to enrich understanding of student perceptions. The results indicate that both groups of students, irrespective of their area of studies, acknowledge the ethical dilemmas introduced by AI in education; however, their concerns vary: while teacher education students are more oriented toward bias, transparency, over-reliance, and equity, business students concentrate on privacy and security. Significant differences were also found in the five ethical categories. The results underscore the impact of disciplinary training on moral reasoning and suggest the value of contextually situated, discipline-specific AI ethics training in higher education. The paper provides recommendations for designing institutional policies that facilitate AI’s responsible and equitable uptake.