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School of Electronic Engineering and Computer Science

A Data-Driven Analysis of the Correlation between English Language Proficiency and Academic Performance in Transnational Education

Dr Chao Shu, Prof Yue Chen and Prof Michael Chai

Best paper award at the TALE 2023 conference

This paper presents a data-driven analysis of the relationship between students' English language proficiency and their academic performance in the context of transnational education. The research is conducted over a comprehensive dataset composed of English module marks, subject-related module results and the overall degree classification marks of the most recent four cohorts of students who have graduated from a UK-China transnational Engineering degree programme. Spearman correlation analysis and hypothesis test was employed to analyse the data and identify patterns and associations between English proficiency and academic performance. Although there is no evidence that suggests causation between the two, our research findings from the data analysis reveal a statistically significant positive correlation between English language proficiency and academic success, with higher proficiency linked to higher degree classifications. Furthermore, our analysis reveals that the impact of English proficiency on academic performance in subject-related modules is more pronounced during the early years of study. The data analytical approach and the resulting insights contribute to the broader understanding of the relationship between English proficiency and academic performance in transnational education, which allows educational institutions to better support students in their language development and overall academic success.

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