In this study, we evaluate how ChatGPT complements and enriches the traditional flipped learning strategy in higher education, particularly in engineering courses. Using an experimental design involving 356 students from basic programming courses in undergraduate engineering programs, we compared the normalized learning gain between groups that used the ChatGPT-assisted flipped learning strategy (focus groups) and those that followed a traditional video-based flipped learning methodology (control groups). The intervention lasted ten weeks, with two sessions of two hours each week. A pre-test–post-test analysis revealed that the focus groups showed significant improvement in normalized learning gain values compared to the control groups. These results confirm that incorporating ChatGPT into the flipped learning strategy can significantly enhance student performance by providing a more active, interactive, and personalized approach during the teaching–learning process. We conclude that the flipped learning strategy, upgraded with the assistance of ChatGPT, provides an effective means to improve understanding and application of complex concepts in programming courses, with potential to be extended to other areas of study in higher education. This study opens routes for future research on the integration of artificial intelligence into innovative pedagogical strategies with the goal of scaffolding the learning experience and improving educational outcomes.