Enhancing Learning and Mitigating AI-Assisted Misconduct: A Case of Using Video Assignments in a High-Enrollment Software Engineering Course

Recent advances in AI-powered writing tools provide powerful support for students but also raise concerns about academic misconduct, especially in large-enrollment courses where monitoring is challenging. To address these concerns, this paper presents a case study on implementing video-based assignments as an alternative to traditional written assessments in an introductory BSc-level Software Engineering course. In this approach, students recorded concise video presentations responding to specific tasks and/or questions, demonstrating both conceptual understanding of course topics and analytical skills — making it more difficult to rely solely on AI-generated text. Survey data and follow-up interviews indicate that this video-based format not only curbed AI-assisted misconduct but also fostered deeper engagement, enhanced communication skills, and reinforced perceptions of fairness in evaluation. These findings underscore the potential of video assignments as a scalable method for mitigating emerging AI-related challenges while enhancing essential soft skills in software engineering education.