Аннотация
This meta-analysis examines the effectiveness of multi-contextual approaches in mathematics learning and explores moderator variables that influence their impact. A total of 27 effect sizes from 14 empirical studies (2015–2023) involving 2,501 students were analyzed using a random effects model via R Studio. Studies were sourced from major academic databases, including ERIC, Scopus, Web of Science, and PubMed. The analysis yielded an overall effect size of 0.65 (p < 0.0001), indicating a substantial impact on students’ mathematical abilities. Moderator analysis revealed that educational level, instructional model combinations, and geographic region significantly influenced effectiveness, while sample size did not. Notably, integrating mathematics with technology and Realistic Mathematics Education (RME) produced the highest effect sizes. These findings support multi-contextual strategies to enhance mathematics learning outcomes and offer valuable insights for educators, curriculum developers, and researchers. The study also highlights the need for future research across diverse educational settings to refine and contextualize effective practices. The study encourages educators to adopt culturally and technologically relevant teaching practices. It also calls for policy support in scaling contextual learning models and investing in teacher training across educational settings.