Rapid technology advancement has profoundly impacted global education systems, particularly in the context of generative artificial intelligence (Gen-AI). This research's objective was to evaluate the potential integration of large language models (LLMs), such as ChatGPT, in chemical engineering education. In a course that employed flipped learning as an active learning strategy, the use of videos as a pre-class preparation activity was replaced by ChatGPT. The study employed a quantitative research design with an exploratory approach, with a sample size of 41 students. The efficacy of integrating ChatGPT was assessed by contrasting the normalized learning gain between the focus and control groups. The results of the descriptive statistics and the t-test indicate that there is no statistically significant difference between the two groups in terms of the normalized learning gain. The principal findings regarding the utilization of ChatGPT in chemical engineering curricula are as follows: first, it has the potential to enhance the explanation of fundamental concepts; second, it presents a challenge in tasks that require complex calculations; and third, it offers an opportunity for developing critical thinking in students. This research contributes to the existing literature on the use of ChatGPT as a tool in flipped classroom and highlights the ongoing need for further work on instructional design. https://repositorio.tec.mx/handle/11285/686283