Research on Intelligent Planning of the Path to Improve Intercultural Communication Competence of Business English in Colleges and Universities Driven by Big Data

Abstract

Aiming at the limitations of the traditional teaching mode and the failure of big data technology to realize the deep integration with the whole process of teaching, the study proposes a cross-cultural communication integration teaching mode based on personalized teaching resources recommendation algorithm. The personalized teaching resource recommendation model proposed in this paper is a personalized teaching resource recommendation method based on cognitive diagnosis and collaborative filtering, MNCD-NMF, which combines multi-factor neurocognitive diagnosis and neural matrix decomposition model to model students' knowledge mastery and obtain students' personalized learning characteristics. Then, the personalized learning characteristics are integrated into the neural collaborative filtering model to predict the students' responses. Finally, a list of recommended learning resources was provided to students by setting different difficulty parameter ranges. Experimental and control classes were designed for teaching practice. The mean values of the four dimensions of intercultural communication competence in the experimental class were 3.45, 3.37, 3.19, 3.23 for the knowledge, awareness and behavior dimensions respectively, and 2.25, 2.29, 2.20, 2.27 for the control class, respectively, and the cross-cultural communication integration teaching model can promote the intercultural communication competence in the knowledge, awareness, affective and behavioral dimensions.