The construction of university English teaching resources is an inevitable requirement to adapt to the development of the times and educational reform. Based on the concept of knowledge and classification, this paper puts forward the theory of Rough set, and applies the idea of partition to the data simplification based on Rough set. Based on the applicability of the partition strategy, the partition idea is added in the process of attribute simplification to achieve the purpose of reducing the complexity of the data simplification algorithm about Rough set. After deriving the decision table, the attribute approximation algorithm based on the attribute order and the partition method is given, i.e., the efficient knowledge approximation method based on the partition method for Rough set. Analyze the performance of Rough set efficient knowledge reduction method based on partitioning method in multiple datasets. To build a knowledge acquisition system platform for university English teaching resources using the efficient knowledge reduction method based on the Rough set of the partition method. In the Heart dataset, the classification accuracies of DIDS method, IV-FS-FRS method, and this paper’s method are 0.5936, 0.5536, and 0.6689, respectively, and this paper’s method outperforms the classification accuracies of DIDS method, IV-FS-FRS method 0.0753, and 0.1153, respectively. The knowledge acquisition system platform of university English teaching resources constructed by using this algorithm has operational advantages in instance analysis.