LEARNING MATHEMATICS IN COMPUTER SCIENCE COURSES: A COMPREHENSIVE STRUCTURED REVIEW

Abstract

Mathematics underpins computer science education, fostering analytical thinking, logical reasoning, and proficient problem-solving abilities. Many students in computer science courses, however, find it challenging to perceive its applicability, which might impede engagement and learning outcomes. This work fills this gap by conducting a systematic review of recent literature on mathematics learning in computer science contexts. Following the PRISMA procedure, a systematic search was performed in two principal databases, Web of Science and Scopus, resulting in 21 primary studies that fulfilled the inclusion criteria. The results were consolidated into three theme categories: technology-enhanced mathematics education, integration of programming and computational thinking, and curriculum and pedagogical innovation. Findings demonstrate that methodologies such as adaptive learning platforms, augmented reality, and flipped classroom models not only improve conceptual comprehension but also elevate student motivation. The study emphasises the necessity of correlating mathematical knowledge with actual programming applications, while also considering learner-related aspects such as motivation, self-efficacy, and mathematics fear. Facilitating fair resource access and integrating mathematics effectively into computer science programs helps prepare graduates with the necessary technical skills and agility to succeed in a swiftly changing digital environment.