<![CDATA[The rapid development of technology, particularly in the field of Big Data, has provided new opportunities to enhance learning processes, including mathematics education. This study explores the utilization of Big Data analytics to analyze and improve mathematics learning outcomes. By processing large-scale educational data, valuable insights can be obtained to identify students' learning patterns, predict academic performance, and develop personalized learning strategies. The research employs a data-driven approach, utilizing machine learning techniques and statistical analysis to examine student performance trends. The findings indicate that the integration of Big Data in mathematics education enables more precise interventions, adaptive learning models, and data-supported decision-making for educators. This research highlights the significance of data analytics in addressing learning challenges, optimizing teaching methodologies, and fostering better educational outcomes. Future studies are recommended to explore more advanced analytical techniques and expand the scope of implementation in various educational settings.]]>
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