USING DATA MINING TECHNIQUES TO SUPPORT STUDENT GROWTH AND DEVELOPMENT

Educational institutions play a vital role in advancing the development and prosperity of the country. A vast array of programs and courses tailored to various academic levels and fields of study are offered by educational institutions. They provide venuesfor social interaction, cross-cultural learning, and personal growth in addition to academic education. The effectiveness of educational institutions is commonly assessed based on attributes including overall learning experience, teacher proficiency, and student success rates.The field of knowledge discovery, which is expanding, extracts knowledge using algorithms, statistics, mathematics, and artificial intelligence. Applying association rules to existing data allows data mining, a crucial stage in Knowledge Discovery in Databases (KDD), to extract knowledge from patterns and correlations. In every field of study, KDD data are used to evaluate and predict future traits. Smart technology development is becoming more and more popular in the field of education. The growing volume of educational data raises the possibility that conventional processing techniques are constrained and skewed. The importance of rebuilding data mining technology in education is growing. Innovative approaches to fostering students' growth and development are required by the evolving educational landscape. In order to maximize student learning outcomes, this study explores the application of data mining techniques as a potent tool for deriving important insights from educational data. Using techniques including data cleaning, integration, categorization, and regression analysis, the paper examines many facets of student performance, such as academic achievement, involvement in extracurricular activities, and behavioral tendencies. By using these insights, the proposed method seeks to gain a comprehensive understanding of students' needs, enabling educational institutions to better tailor interventions and support systems. Utilizing data mining techniques has the potential to transform student growth and development as education adopts technological advancements, resulting in a more customized and adaptive learning environment.