With the advent of the information age, digital literacy has become an indispensable foundational skill in modern agricultural production, particularly for farmers. To enhance farmers' digital literacy, the development of an efficient interactive learning system is of utmost importance. This study focuses on designing an interactive learning system tailored for farmers. By conducting an in-depth analysis of behavioral patterns in human-computer interaction, a new learning model based on human-computer behavior was constructed, and the system's algorithms were optimized accordingly. The paper first introduces the system's design and functional requirements, analyzing the digital literacy needs of the farmer population; then, it details the specific methods of human-computer behavior modeling, combining farmers' operational habits and learning characteristics to propose targeted optimization algorithms; Finally, the user experience and learning effectiveness of the system are evaluated through empirical analysis. The results indicate that the optimized system significantly improves farmers' digital literacy levels, particularly in terms of learning efficiency and operational convenience. This study not only provides strong support for enhancing farmers' digital literacy but also offers new insights and methods for optimizing interactive learning systems.
Zhou et al. (Sun,) studied this question.