Arlene O. Borbon and Regina P. Galigao (Authors)
Abstract
This study investigates the impact of social class, gender, and race on educational inequalities across regions using a data mining approach. By analyzing large datasets from academic journals, official reports, and institutional databases, it identifies key barriers to access and academic success. Findings reveal that financial and institutional constraints hinder social mobility for lower-income students, cultural norms drive gender disparities, and systemic bias limits opportunities for racial minorities. Using both quantitative and qualitative methods, the study uncovers patterns in inequities and highlights the need for inclusive policies to promote equitable education for all.
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Keywords: Educational inequalities, Data mining approach, Systemic barriers, Social mobility, Gender disparities, Racial bias