A Bayesian network-based study of the correlation between students’ study habits and foreign language performance

Abstract

Abstract Exploring the relationship between students’ study habits and foreign language performance is of great significance to the field of education, this paper investigates the correlation between students’ study habits and foreign language performance, and uses Bayesian networks to construct a labeled correlation model of study habits and their effects on foreign language performance. A multi-labeled Bayesian network model was built to assess the impact of different study habits on foreign language achievement by collecting and analyzing data on study habits and foreign language achievement of 110 college and university students. In this study, there was a significant positive correlation between the characteristics of learning behaviors in class (e.g., pre-study and review) and foreign language achievement, with correlation coefficients of 0.366 and 0.411, respectively, while the association between the characteristics of life behaviors (e.g., sleep and diet) and foreign language achievement was relatively weak. The study also showed a high positive correlation (0.283) between positive attitudes towards school and foreign language achievement. Through Bayesian network analysis, this paper further confirms the importance of good study habits in improving academic performance in foreign languages. By optimizing students’ study habits and extracurricular learning behaviors, the study can effectively enhance foreign language learning outcomes.