College and university English courses rely heavily on the logical application of context building; nonetheless, students often make mistakes in identifying relevant situations. Using a conventional evolutionary algorithm to build scenarios for use in college English classes yields unsatisfactory results. Consequently, this study suggests and examines a rational application analysis of scenario creation in college English teaching based on association rule mining algorithm. It also analyzes to minimize interference with the logical application of scenario creation, we first utilize network analysis theory to identify the components that have an impact, and then we split the indicators based on what is needed. Next, we create plausible application schemes by using the theory of network analysis to the formation of association rules. Then, we construct suitable application outcomes by completely analyzing scenarios and mining algorithm scenarios. The results of the MATLAB simulations reveal that, according to specific evaluation criteria, the association rule mining algorithm outperforms the conventional genetic algorithm when it comes to the reasonableness of scenario construction accuracy and the reasonableness of influencing factor scenario construction time.