A Comprehensive Data Science Framework forEnhancing Public School Education: IntegratingPredictive Analytics, Machine Learning, andVisualization Techniques

Abstract

The integration of data science into public education systems presents unprecedented opportunities for enhancing learning outcomes, optimizing resource allocation, and informing policy decisions. This paper proposes a comprehensive framework for leveraging data science methodologies in public schools, encompassing predictive analytics, machine learning, and data visualization techniques. By analyzing large-scale educational datasets, we demonstrate the potential for data-driven insights to improve student performance, personalize learning experiences, and streamline administrative processes. This research provides a roadmap for educational institutions to harness the power of data science, ultimately contributing to the advancement of public education systems