Enhancing AI Code Detection in Education

This assessment explores the transformative impact of large AI models on programming education, including detection challenges. Outcomes reveal detectors struggle with distinguishing AI-generated code, showing just 50% accuracy and vulnerability to modifications. Innovations involve testing detectors empirically, analyzing characteristics impeding detection, and utilizing statistical measures to highlight flaws. Recommendations emphasize developing code-specific tools, ethical AI policies,...