A Framework for Assessment Design in the Era of Generative AI: Case Study of Take-Home Assignment in Software-related Courses

The use of Generative Artificial Intelligence (Gen-AI) in education has introduced various challenges, especially in assessment design, particularly concerning academic integrity. A major concern is plagiarism, as students can easily use AI-generated content to cheat on assignments, undermining the credibility and reliability of assessment results. This paper proposes a framework for designing take-home assignments in software-related courses incorporating Gen-AI while promoting academic integrity. The research employs an experimental approach and provides qualitative analysis by focusing on three carefully selected courses from the BIT and BSE programs. The framework offers guidelines for creating assignments that curtail plagiarism and ensure alignment with course learning objectives. The proposed framework suggests designing assessments between 3-6 levels of Bloom’s taxonomy to integrate Gen-AI into assessments while preserving its academic integrity.