The Path of a Computer-Supported Collaborative Learning Approach Based on Data Mining Techniques to Promote Students' Intercultural Communication Competence in the English Language Discipline

Abstract

Computer-supported collaborative learning (CSCL) methodology can facilitate communication among learners in online learning platforms. This study proposes a practical strategy for English majors to apply CSCL teaching model and students' cross-cultural communication competence cultivation. By mining the characteristics of students' learning behaviors, combined with an improved density clustering algorithm, collaborative learning cluster construction is realized. Finally, practice teaching is carried out to verify its effectiveness from the improvement of students' intercultural communication ability. Through the paired-sample test of the knowledge dimension of the experimental class and the control class, it is found that the paired-sample t-test results of the pre and post-tests of the knowledge dimension of the experimental class show that T=-18.605, P=0.000, and the P-value is lower than the significance of 0.05, which can be obtained that there is a significant difference between the performance of the pre and post-tests of the experimental class before and after the experiment, and that the post-tests of the experimental class are superior to the pre-tests, which leads to the conclusion that based on the The computer-supported writing learning method based on data mining technology plays a positive role in the improvement of students' intercultural communication skills.