Assessment Design Before and After the Emergence of Generative AI

The birth of generative AI has had a profound impact on assessment design in the field of software programming courses. This study investigates the changes in assessment methodologies before and after the emergence of generative AI technology. Traditional assessment approaches in programming courses often involved manual code reviews, quizzes, and practical assignments. However, with the advent of generative AI, new assessment methods have emerged, leveraging automated code analysis, intelligent feedback generation, and adaptive testing. This abstract highlights the paradigm shift in assessment design, emphasizing the potential benefits of generative AI in enhancing assessment accuracy, efficiency, and personalized learning experiences for software programming students. By examining the evolution of assessment practices in the context of generative AI, this study aims to contribute to the ongoing discussions on the integration of AI technologies in software programming education.