Educational Knowledge Discovery : A Quality Assurance Analysis of Academic Results Employing Data Mining - Dr. Pardeep Arora; Avleen Kaur; Mandeep Kaur, Mandeep Kaur (International Journal of Scientific Research in Science and Technology, 2024)
This paper explores the multifaceted aspects of improving academic performance through detailed data analysis, diverse teaching methods, student engagement, and parental involvement. By examining the impact of traditional and innovative teaching strategies, the study highlights the benefits of combining structured and interactive approaches to enhance learning. The crucial role of student engagement and parental support in boosting academic success is also discussed. Additionally, the paper delves into the transformative potential of data mining and machine learning in education, illustrating how these technologies can uncover valuable insights and predict student performance trends. This comprehensive approach aims to provide a robust framework for educators to optimize educational outcomes and foster a more effective learning environment.
Keywords: Academic Performance Improvement; HAOA Project; Teaching Methods; Student Engagement; Parental Involvement; E-KDD; Data Analysis; Data Mining; Machine Learning; Predictive Models; Educational Technology; Personalized Learning; Clustering algorithm