The literature and terminology of vocational schools heavily rely on studies of educational decision-making systems; nonetheless, there is a problem with incorrect performance positioning in these studies. When applied to vocational school language and literature, conventional particle swarm algorithms fail to resolve the decision-making system problem. Study on the Decision System of Language and Literature Education in Vocational Schools Based on Apriori Algorithm is reviewed and an Apriori algorithm-based study on the same is presented. In order to reduce interference variables in the research of educational decision-making systems, we first utilize frequent item set mining theory to uncover the influencing aspects. Then, we separate the indicators depending on the demands of the study. Afterwards, an Apriori algorithm research of educational decision-making system scheme is developed using the frequent item set mining theory, and the results of this study are carefully evaluated. The Apriori method beats the conventional Particle swarm math under certain assessment settings, according to the MATLAB simulation findings, when it comes to studying educational decision-making systems in terms of accuracy and time of influencing factors.