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ABSTRACT The integration of chatbots and generative artificial intelligence (AI) tools into engineering education is rapidly changing the way students learn, interact, and solve complex problems. These technologies offer new opportunities for personalized learning, real‐time feedback, and enhanced student engagement. However, a comprehensive understanding of their implementation, pedagogical value, and limitations in engineering education remains limited. This structured literature review examines how chatbots and generative AI tools are integrated into engineering education and evaluates their educational impact and associated challenges. The review focuses on their effects on student learning outcomes, engagement, and skills development, as well as the challenges associated with their implementation. Following PRISMA guidelines, literature was identified through Scopus, Google Scholar, Taylor & Francis Online, and ScienceDirect. After applying predefined inclusion criteria, 16 studies were included in the final review and were analyzed thematically. The findings show that chatbots and generative AI tools can improve learning outcomes in engineering education by promoting student engagement, supporting conceptual understanding, encouraging self‐directed learning, and contributing to the development of problem‐solving and creative thinking skills. However, the review also identifies challenges related to ethical concerns, accuracy limitations, and the risk of student overreliance, which can impact the development of deeper learning and collaboration. 

Engineering projects, such as designing a solar farm that converts solar radiation shined on the Earth into electricity, engage students in addressing real-world challenges by learning and applying geoscience knowledge. To improve their designs, students benefit from frequent and informative feedback as they iterate. However, teacher attention may be limited or inadequate, both during COVID-19 and beyond. We present Aladdin, a web-based computer-aided design (CAD) platform for engineering design with a built-in artificial intelligence teaching assistant (AITA). We also present two curriculum units (Solar Energy Science and Solar Farm Design), where students explore the Sun-Earth relationship and optimize the energy output and yearly profit of a solar farm with the help of the AITA. We tested the software and curriculum units with over 100 students in two Midwestern high schools. Pre- and post-survey data showed improvements in understanding of science concepts and self-efficacy in engineering design. Pre-post analysis of design performance gains reveals that AI helped lower achievers more than higher achievers. Interviews revealed students’ values and preferences when receiving feedback. Our findings suggest that AITAs may be helpful as an additional feedback mechanism for geoscience and engineering education. Future efforts should focus on improving the usability of the software and providing multiple types of feedback to promote inclusive and equitable use of AI in education. 

First-year engineering students are often introduced to the engineering design process through project-based learning situated in a concrete design context. Design contexts like mechanical engineering are commonly used, but students and teachers may need more options. In this article, we show how sustainable building design can serve as an alternative for students of diverse backgrounds and with various interests. The proposed Net Zero Energy Challenge is an engineering design project in which students practice the full engineering design cycle to create a virtual house that generates renewable energy on-site, with the goal to achieve net zero energy consumption. Such a design challenge is made possible by Aladdin, an integrated tool that supports building design, simulation, and analysis within a single package. A pilot study of the Net Zero Energy Challenge at a university in Mid-Atlantic United States suggests that around half of the students were able to achieve the design goal. 

Video analysis tools such as Tracker are used to study mechanical motion captured by photography. One can also imagine a similar tool for tracking thermal motion captured by thermography. Since its introduction to physics education, thermal imaging has been used to visualize phenomena that are invisible to the naked eye and teach a variety of physics concepts across different educational settings. But thermal cameras are still scarce in schools. Hence, videos recorded using thermal cameras such as those featured in “YouTube Physics” are suggested as alternatives. The downside is that students do not have interaction opportunities beyond playing those videos.