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Entrepreneurial competence is a critical skill for twenty-first-century learners, yet effective instructional models for fostering this ability remain underexplored. This study investigates the impact of an AI-assisted, argumentation-driven learning approach on the development of entrepreneurial competence among university students. Utilizing a quasi-experimental design, 86 students participated in a scientific argumentation-driven entrepreneurship education course, with one group receiving Generative Artificial Intelligence (GAI) support and the other following a traditional instructional approach. Structural Equation Modeling (SEM) results revealed that data literacy played a pivotal role in predicting entrepreneurial competence, acting as a mediator between AI assistance, teacher guidance, and students’ ability development. Additionally, Fuzzy-Set Qualitative Comparative Analysis (fsQCA) identified seven distinct paths to entrepreneurial competence, highlighting the interplay between cognitive and environmental factors. The findings underscore the transformative potential of AI-assisted learning models in enhancing entrepreneurial competence, providing insights for the personalization of entrepreneurship education and the promotion of educational equity.
Zhou et al. (Sun,) studied this question.