Promoting Responsible Generative AI Use in Academic Writing: Academic Integrity,Ethical Judgement, And Student Practice
Abstract
The increasing use of Generative Artificial Intelligence (GenAI) in higher education has changed the academic writing practices of students, presenting both opportunities to improve learning and challenges to academic integrity. The study explored the relationship between the GenAI use profile, academic integrity awareness, ethical judgment and decision-making, and responsible GenAI use practices in academic writing of fourth-year students of North Eastern Mindanao State University (NEMSU). It examined students’ awareness of risks to academic integrity associated with GenAI, ethical judgment and decision-making in GenAI-assisted writing, and responsible AI-use practices. The study also explored the lived experiences and perceptions of students on ethical use of GenAI in academic writing. A descriptive correlational design was employed. The quantitative data were collected from 303 fourth-year students selected using simple random sampling. Descriptive statistics and Pearson Product-Moment Correlation were used to analyze the data. The findings revealed that respondents were generally moderately aware of GenAI-related academic integrity risks, exhibited moderately manifested ethical judgment and decision-making, and demonstrated moderately practiced responsible GenAI use behaviors. Significant relationships were found between GenAI use profile and academic integrity awareness, academic integrity awareness and ethical judgment and decision-making, and ethical judgment and decision-making and responsible GenAI use practices. These findings suggest that while students possess foundational knowledge and ethical awareness regarding GenAI use, gaps remain in translating awareness into consistently responsible practices. The study underscores the need for comprehensive AI literacy programs, explicit institutional guidelines, and ethics-focused educational interventions that promote transparency, accountability, critical evaluation, and responsible human oversight in AI-assisted academic writing.