Educational Knowledge Discovery : A Quality Assurance Analysis of Academic Results Employing Data Mining

Dr. Pardeep Arora; Avleen Kaur; Mandeep Kaur Mandeep Kaur

doi:10.32628/IJSRST24113235

Authors

Dr. Pardeep Arora Associate Professor, PG Department of Computer Science and Applications, Kanya Maha Vidyalaya, Jalandhar, Punjab, India Author
Avleen Kaur M.Sc. (Computer Science), Kanya Maha Vidyalaya, Jalandhar, Punjab, India Author
Avleen Kaur M.Sc. (Computer Science), Kanya Maha Vidyalaya, Jalandhar, Punjab, India Author

DOI:

https://doi.org/10.32628/IJSRST24113235

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

Abstract

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.

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References

https://christcollegeijk.edu.in/uploads/userfiles/result%20analysis%20initiative.pdf

A. G. Balim, "The Effects of Discovery Learning on Students’ Success and Inquiry Learning Skills", 2009.

Yueh-Min Huang, Yen-Ting Lin, Shu-Chen Cheng b, "An adaptive testing system for supporting versatile educational assessment", 2009. DOI: https://doi.org/10.1016/j.compedu.2008.06.007

Hao Lei, Yunhuo Cui, Wenye Zhou, "Relationships Between Student Engagement And Academic Achievement: A Meta-Analysis", 2018. DOI: https://doi.org/10.2224/sbp.7054

Xitao Fan, Michael Chen, "Parental Involvement and Students' Academic Achievement: A Meta-Analysis", 1999.

Ashish Dutt, Maizatul Akmar Ismail, Tutut Herawan, "A Systematic Review on Educational Data Mining", 2017. DOI: https://doi.org/10.1109/ACCESS.2017.2654247

https://www.javatpoint.com/data-mining-cluster-analysis.

Ahmed Mueen, Bassam Zafar, Umar Manzoor, "Modeling and Predicting Students’ Academic Performance Using Data Mining Techniques", 2016. DOI: https://doi.org/10.5815/ijmecs.2016.11.05