Envisioning the future of learning and teaching engineering in the artificial intelligence era: Opportunities and challenges

Generative artificial intelligence (AI) technologies, such as large language models (LLMs) and diffusion model image and video generators, can transform learning and teaching experiences by providing students and instructors with access to a vast amount of information and create innovative learning and teaching materials in a very efficient way (e.g., U.S. Department of Education, 2023; Kasneci et al., 2023; Mollick & Mollick, 2023; Nikolic et al., 2023). For example, Google Bard and OpenAI ChatGPT are LLMs that can generate natural language texts for various purposes, such as summaries of research papers (e.g., OpenAI, 2023). At the same time, Midjourney and DeepBrain AI are diffusion models that can create diagrams (e.g., concept maps), images, and videos from textual or visual inputs. Engineering education, in particular, can benefit from integrating and utilizing generative AI technologies to improve instructional resources, develop new technology-enhanced learning environments, reduce instructors' workloads, and provide students with opportunities to design and develop their learning experiences. These technologies can help educators to create more personalized, effective, and engaging learning experiences for engineering students. Most engineering students struggle to acquire a deep understanding of complex engineering concepts because of the nature of the highly mathematical concepts, lack of prior knowledge, limitations of the large lectures, limited resources that prevent the use of commercially available lab equipment, and the lack of innovative teaching tools that could be utilized to enhance learning experiences (e.g., Menekse et al., 2018, 2022; Miller et al., 2011; Reeves & Crippen, 2021; Streveler & Menekse, 2017). These factors adversely affect retention and graduation rates and inhibit persistence in engineering majors (e.g., Estrada et al., 2016). Generative AI technologies and tools (e.g., CourseMIRROR) could support engineering educators to improve students' learning and engagement (e.g., Fan et al., 2015; Luo et al., 2015; Menekse, 2020).