College Students on Generative A.I.: Basis for Ethical Generative A.I. Utilization Policy

Abstract

The rapid emergence of generative artificial intelligence (AI) has significantly transformed higher education, providing innovative tools for enhanced learning and scholarly practices while also raising ethical concerns.​ ​The study examines college students' perceptions of generative AI in education, highlighting the need for ethical utilization policies.​ Generative AI transforms learning by offering personalized experiences and enhancing research skills while posing ethical challenges, such as threats to academic integrity and potential biases. The study aims to understand student perceptions, assess their knowledge and willingness to use AI and develop policies for responsible AI usage in higher education. The research employs a descriptive quantitative design, gathering data from students across various departments in a Philippine Catholic institution. It identifies trends in AI tool usage, with ChatGPT and Canva being frequently used, indicating a shift towards multimodal learning. However, ethical guidelines are emphasized due to concerns about privacy, plagiarism, and the risk of fostering over-reliance on AI. The theoretical framework incorporates the Technology Acceptance Model and Cognitive Load Theory to explore students' engagement with AI tools, recognizing both the potential for enhanced learning and the need for balanced cognitive load management. The findings reveal a moderate awareness of AI's limitations and ethical concerns, such as biases and misinformation, suggesting that educational policies should address these issues. Additionally, students demonstrate a strong consensus on the necessity of ethical guidelines regarding transparency and accountability, indicative of a demand for enhanced media literacy and AI detection training. The study proposes institutional policy recommendations, including AI literacy workshops, curriculum integration, and the establishment of an ethical generative AI framework, underscoring the importance of interdisciplinary collaboration in addressing concerns while maximizing the benefits of AI in educational contexts.