Utilizing Big Data Analytics and AI for Personalized Learning in Mathematics Education

Applying big data analytics to mathematics education is done to improve the overall results of learning and eliminate the drawbacks of conventional approaches. These are a lack of individualization, each response not being immediate, and poor approaches to engaging clients. Solutions include creating technologies focusing on adaptive learning and data analytics for more appropriate education. The proposed solutions are quite realistic, as shown in the example of Arizona State University, where the implementation of given concepts led to an increase in performance levels and the rates of students' attendance. However, for it to be implemented, there is a need to improve the technical infrastructure for enhanced data flow and address data privacy issues. The targeted approaches to the utilization of big data analysis can significantly enhance the learning of mathematics to provide for improved accessibility by discriminated learners.