MOBILE LEARNING ANALYSIS IN COMPUTER SCIENCE: A SYSTEMATIC REVIEW OF THE IMPACT AND FACTORS ON STUDENT LEARNING OUTCOMES - Erlangga Erlangga; Alya Nurfaridah; Erna Piantari; Muhamad Dzikri Gumilang; Muhammad Riza Abqari; Raka Ibnu Firdaus (Journal of Computer Science and Information Technology, 2025)
Limited access and flexibility in higher education, particularly in the field of Computer Science which demands analytical and technical skills, necessitate a more adaptive learning approach. This study aims to examine the influence of M-Learning on student learning outcomes and identify critical success factors (CSFs) that affect its implementation. The method used is a Systematic Literature Review (SLR) through the planning, implementation, and reporting stages, with a publication range of 2020–2025. Analysis of ten studies showed that M-Learning significantly improved learning outcomes, motivation, and independence, especially for programming-based and applied science materials. This effectiveness is influenced by the quality of the pedagogical design, active learning approaches, and adequate technological support. This finding confirms that M-Learning is a relevant and effective learning strategy, with its success heavily dependent on pedagogical factors and infrastructure readiness.