In this paper, we first constructed an online interactive English teaching model through the interaction hierarchy tower model and adopted a data-driven social cognitive network analysis approach to explore the evolutionary dynamics of cross-border e-commerce English learning communities in higher education and their potential correlation with the development of participants’ interaction patterns. Then, the online synchronous and asynchronous interaction patterns of learners are compared and integrated by extracting the characteristics of online interactive teaching learners. Finally, an instructional design for an online English for Cross-border E-commerce course was used to explore the differences and associations between online interactive teaching modes. The results show that in the teaching experiment, students have 39 nodes in the synchronous interaction network (SMN) and 34 nodes in the asynchronous interaction network (UMN), and the degree centrality and eigenvector centrality Rank=4.07 and 3.15 of the SMN are also significantly higher than those of the three interaction networks. The SMN interaction model is found to be the most efficient in the online interaction teaching process. This study helps to improve the dynamic regulation and precise guidance of the online learning process for cross-border e-commerce English, which ultimately enhances the quality of online teaching.