Generative AI in Engineering Education

Abstract

The recent development in the ability and availability of generative artificial intelligence (GenAI) has challenged the status quo in higher education. Consequently, we investigate the multifaceted integration of GenAI into engineering education in order to identify the successful strategies to empower learners and educators, while overcoming ethical and academic integrity concerns. To do so, we offer a review and analysis of the recent literature (post-ChatGPT) to ascertain the opportunities and challenges associated with GenAI. Our review focuses on key dimensions such as adaptability, ethical considerations, pedagogical implications, industry collaboration, adaption of soft skills and lifelong learning, assessment and feedback methods. Furthermore, GenAI technologies, including natural language processing and computer vision, offer innovative possibilities for personalised learning experiences, content generation, and problem-solving. This study examines best practices and innovative strategies for incorporating GenAI into engineering education and proposes effective solutions. It is anticipated this paper will support educators and institutions in employing GenAI technologies to improve engineering education.