The Impact of Prior English Learning on the Academic Success of Computer Science Students

This article examines the impact of students’ prior experience with English on their academic success in a university English course. The study is based on a survey conducted among students majoring in Computer Science, Business Information Technology (BIT), and Software Technology and Design (STD) at the Faculty of Mathematics and Informatics (FMI), University of Plovdiv, at the beginning of their general English language course. We focus on students’ self-assessed language competence at the start of the course and examine how these self-assessments correspond to their actual test results. Using high-performance machine learning methods, we identify background factors that influence academic achievement, including the number of years spent learning English, the type of high school attended, and informal exposure to English. The findings aim to support more effective and tailored approaches to teaching English in technical and scientific disciplines.