Using a mixed-methods approach, data were collected from 1,483 students and 95 teachers through random and purposive sampling. The findings indicate adaptive learning technologies significantly improve student performance by tailoring instruction to individual needs. Real-time educational data analysis enables early identification of disengagement, facilitating timely interventions. Additionally, insights into student interaction patterns inform the development of evidence-based teaching strategies that foster critical thinking and problem-solving skills. The study highlights the transformative role of educational data mining in creating immersive learning environments that enhance conceptual understanding and practical application, reducing achievement gaps among diverse student populations.
