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 (Yayasan Nuraini Ibrahim Mandiri, 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.