Data-Driven Education: Data Processing as a Key to Improving the Quality of Mathematics Education

Abstract

Education is a major pillar in the development of a nation, and the quality of education becomes a key factor in determining the progress of a society. In this digital era, there is a rapid development in the use of information technology, and this has a significant impact on the education sector.  The purpose of this study is for data-driven education: data processing as the key to improving the quality of mathematics education. This research uses a mixed method that combines qualitative and quantitative methods. This approach was chosen to address the complexity of data management and the comprehensiveness of this topic. The research begins with an in-depth literature analysis to understand the potential of Data-Driven Education. By using data as a guide, educators can make smarter decisions, detail instructional strategies, and create an educational environment that allows each student to reach his or her full potential. This is done by combining the results of various data of educator learners who can make informational decisions to improve the quality of mathematics learning. The application of data management in the context of mathematics education can provide concrete solutions to overcome challenges and improve the quality of learning. The right use of data provides the basis for smarter decisions and more adaptive learning, creating a learning environment that fits the needs of each student. By integrating Data-Driven Education effectively, we can move towards a more inclusive, personalized and successful mathematics education. The use of data contributes significantly in improving the quality and inclusivity of mathematics education. The integration of data management in mathematics education is a critical step towards a more adaptive, inclusive, and effective education