Su Yue

The rise of generative AI poses significant challenges to traditional academic assignments, particularly in higher education, by influencing teaching methodologies and student learning behaviors. This study explores how to effectively guide students in critically collaborating with AI during assignment completion to enhance efficiency while ensuring originality and depth. Conducted within the "Science and Technology News Writing" undergraduate course, students were tasked with writing an in-depth report on "intelligent driving," integrating information from various sources. Guidelines permitted AI use for information retrieval, data queries, and preliminary idea generation but prohibited direct copying of unchecked AI-generated text. Students were required to verify all factual information provided by AI and submit an AI interaction log alongside a written rationale for their decisions regarding AI suggestions. Data collection involved analyzing final submissions, AI logs, reason statements, and conducting semi-structured interviews with 24 selected students. Expected outcomes include enhanced critical thinking and independent judgment skills, improved academic integrity through clearly defined AI usage boundaries, and increased recognition of the teaching model incorporating AI technology. Despite initial technical and cognitive challenges, feedback indicates that this approach offers new learning perspectives, improves classroom interaction, and boosts engagement. This research provides insights into balancing AI's potential as an auxiliary tool with maintaining high standards of academic output.