Background and Objectives:This study
school mathematics learning during the 2023–2024 academic year. Methods: This was an applied research study employing a mixed-methods (qualitative-quantitative) approach with a sequential-exploratory design for data collection. In the qualitative phase, a meta-synthesis approach was utilized, following the method proposed by Sandelowski and Barros (2007). The statistical population for this initial phase comprised 75 domestic and foreign scientific articles and texts. Following a screening process, 45 articles were analyzed using open coding.The quantitative phase involved developing a matrix questionnaire for weighting and ranking the identified influential factors. This questionnaire was administered to 10 experts selected through purposeful sampling. Data analysis and the factor ranking process were conducted using a Fuzzy Multi-Criteria Decision-Making (MCDM) technique, specifically the fuzzy cognitive mapping method. Findings: The results indicated that four factors—practical application of teaching, intervention protocols, integration in the mathematics curriculum, and the use of active and participatory teaching methods in mathematics education—possessed the highest in-degree (i.e., greatest incoming influence), respectively. Furthermore, the factors integration of the mathematics curriculum, attention to local culture and language in mathematics education, attention to logical-mathematical thinking in the learning process, and the use of active and participatory teaching methods in mathematics education exhibited the highest centrality degree (i.e., overall importance within the network), respectively. Conclusion: By identifying the factors influential in mathematics learning, it is possible to improve teaching methods, educational content, and curricula, thereby enhancing the quality of mathematics education. These influential factors can assist educational policymakers in making more informed decisions regarding teacher training and the design of educational programs