The Application of Artificial Intelligence in Engineering Education: A Systematic Review - Cong Liu; Guang-Chao Wang; Hong-Feng Wang (IEEE Access)
Artificial Intelligence (AI) is increasingly impacting the environment, pedagogy, and management practices in engineering education. However, literature reviews that provide a systematic review and analysis of AI in engineering education remain limited. To address this research gap and gain a comprehensive understanding of AI applications in engineering education, this study conducts a systematic review based on 161 studies on AI applications in engineering education. Using VOSviewer, this paper analyzes the research hotspots of AI in engineering education, as well as the top ten organizations, countries, cited sources, and cited authors. Furthermore, the study categorizes the application of AI technologies in engineering education into seven distinct categories: Virtual Experiment Environments, Learning Prediction, Learning Analytics, Engineering Education Robots, Intelligent Tutoring Systems, Automatic Evaluation, and Assisted Learning. The study reveals that these technologies have already been widely adopted. Moreover, this paper summarizes the influence of AI technologies on engineering education, along with the implications and challenges, providing a foundation for further exploration of the integration of AI technologies into educational systems.