Examining the impact of higher-order thinking and GAI chatbots on engineering creativity in higher education

The development of higher-order thinking and creativity is widely regarded as a central objective in engineering education. With the increasing use of generative artificial intelligence (GAI) tools, particularly AI chatbots, there is growing interest in understanding how these technologies are related to cognitive processes and creative outcomes. This study examines the relationships among higher-order thinking, GAI chatbot use, and engineering creativity, with a particular focus on their underlying dimensions. Data were collected through a self-reported survey administered to engineering students, and the proposed model was analyzed using partial least squares structural equation modeling (PLS-SEM). Importance–performance map analysis (IPMA) and necessary condition analysis (NCA) were also conducted to provide complementary perspectives. The results indicate that higher-order thinking is positively associated with engineering creativity and with reported GAI chatbot use. In contrast, the association between GAI chatbot use and engineering creativity is comparatively weaker, although statistically significant. The IPMA results show that higher-order thinking has higher relative importance within the model, while GAI chatbot use demonstrates moderate performance but lower importance. The NCA findings further suggest that certain dimensions of higher-order thinking may act as constraints at lower levels of creativity. The findings highlight differentiated relationships among cognitive processes, AI tool use, and creativity in engineering education. The study contributes to a more fine-grained understanding of how higher-order thinking and AI tool use are related to different aspects of engineering creativity.