Addressing Sustainability Challenges in AI Integration: Data Privacy, Accessibility, and Ethical Considerations

This paper explores the integration of AI-based assessment techniques in engineering education, highlighting their potential to enhance personalized feedback, improve learning outcomes, and streamline assessment processes. It examines various AI tools and their applications in automated grading, adaptive testing, and intelligent tutoring systems. Additionally, it addresses the challenges of implementing AI in educational settings, including fairness, data privacy, and integration with existing systems. The paper concludes with a discussion on strategic planning and continuous improvement to optimize AI's role in fostering an effective assessment framework for engineering education.