LEVERAGING GENERATIVE AI TO ENHANCE ENGINEERING EDUCATION AT BOTH LOW-LEVEL AND HIGH-LEVEL STUDY

Abstract

Generative Artificial Intelligence has revolutionized various sectors, including engineering education.This paper explores the integration of Generative AI tools into engineering curricula, focusing on their potential to enhance project-based learning (PBL), foster creativity, and offer personalized learning experiences.By leveraging Generative AI, educators can provide tailored feedback, promote knowledge expansion, and facilitate hands-on learning, addressing challenges faced by both lower-level and advanced engineering students.This study investigates the outcomes of implementing Generative AI in courses such as Circuit Analysis, Dynamics, Electrical Power, and Industrial Power.Results indicate that students achieved significant improvements in project quality, depth, and originality.However, the paper also highlights ethical concerns, particularly regarding plagiarism, algorithmic bias, and data privacy.Through a comprehensive analysis, the study underscores the transformative potential of Generative AI while advocating for ethical guidelines to ensure responsible usage in engineering education.Future work will focus on developing robust plagiarism detection tools and refining the ethical frameworks for AI integration in educational settings.

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