University Learning Analytics in the Age of Big Data: The Case of the Chinese Educational System

ABSTRACT In recent years, the integration of big data and learning analytics has emerged as a significant trend across educational systems worldwide. The implementation of such technologies within universities – particularly in China – holds considerable potential for transforming teaching and learning practices. By enabling personalised, data‐driven insights, these innovations can enhance student learning outcomes and overall academic performance. The study aims to evaluate the effect of the LeMo learning analytics platform on students' English language performance and their motivation. The experiment enrolled 181 students from the Yellow River Conservancy Technical Institute. It demonstrated that the students of the experimental group were more successful in the English language exam (M = 13.51) versus the control group without intervention (M = 9.69); they also had higher motivation (M = 4.17) than the control group (M = 3.08). All differences were statistically significant and confirmed the positive effect of the LeMo. The findings of this experiment can be an important guide and resource for building learning analytics services to support educational practice. Also, teachers can use them to ensure the proper quality of online education and the development of educational courses and curricula to increase the efficiency and effectiveness of the learning process.