Against the backdrop of deep AI-agriculture integration, smart agriculture has become a key direction for agricultural modernization, demanding higher digital-intelligent learning competence from university students. As a core competency for leveraging AI to engage in agricultural information technology learning and solve practical problems, the mechanisms underlying its formation remain underexplored. This study targets undergraduate and graduate students in smart agriculture-related majors, constructing a theoretical model based on the dual dimensions of external technological characteristics and internal learning processes. It systematically investigates how key factors—including the te... More >