Abstract:  Currently, there are several issues in teacher and student political theory learning, such as in-sulficient relevance and lack of refined management. This paper explores the application of associationrule mining technology in teacher and student politieal theory learning. By analyzing and extracting thecharacteristies of teacher and student learning objects, the paper mines the relationships between thesefeatures using association rule algorihms. Based on the results , differentiated and targeted learning strat.egies are implemented. Firstly, a problem model is established. Secondly, the Apriori algorihm is applied to mine association rules from the dataset. Additionally, an optimization algorithm using pruningtechniques is proposed to accelerate rule generation and improve algorithm elficiency. Finally, extensiveexperiments are conducted to verily the effectiveness of the problem model, algorithms, and pruning tech-niques.