While Active Learning (AL) approaches, including debates and discussions, have gained prominence in recent years, issues concerning student engagement and performance persist in educational environments. Based on the perceived experiences of the teaching body in university classrooms at the bachelor’s level, our hypothesis suggests that these challenges may stem from students’ limited critical thinking capabilities, a lack of perceived applicability of knowledge, and insufficient curiosity. Using the framework of AL Resistance (ALR) and suggested methods of remediation, a university course integrating resistance-reducing AL methods was designed. Different AL methods were applied. Here, we will explore specific results regarding the application of a tool backed by Artificial Intelligence (AI). Specifically, generative Large Language Models (LLMs) were used to promote critical thinking, engagement, and curiosity. This study investigates the outcomes of this innovative approach and its potential to bridge the theory-practice divide in education.