Exploring Student Academic Performance Using Data Mining Tools


  • Ranjit Paul North Lakhimpur College
  • Silvia Gaftandzhieva University of Plovdiv “Paisii Hilendarski”
  • Samina Kausar Shanghai University
  • Sadiq Hussain Dibrugarh University
  • Rositsa Doneva University of Plovdiv “Paisii Hilendarski”
  • A.K. Baruah Dibrugarh University




datasets, quality evaluation, data mining, student academic performance, educational data mining


Most of the educational institutes nowadays benefited from the hidden knowledge extracted from the datasets of their students, instructors and educational settings. The education system has gone through a paradigm shift from a traditional system to smart learning environments and from a teacher-centric system to context-aware any time anywhere student-centric approach. In this changing scenario, we have undertaken a study to investigate the results, grades and patterns of the students of North Lakhimpur College. The paper aims to evaluate the quality of learning on the basis of 19249 grades received from 758 students in 511 courses, included in the curriculum of 3 study programmes.

Author Biographies

Ranjit Paul, North Lakhimpur College

North Lakhimpur College

Silvia Gaftandzhieva, University of Plovdiv “Paisii Hilendarski”

Department of Computer Science Assistant Professor

Samina Kausar, Shanghai University

Shanghai University

Sadiq Hussain, Dibrugarh University

Dibrugarh University System Administrator

Rositsa Doneva, University of Plovdiv “Paisii Hilendarski”

ECIT Department Professor

A.K. Baruah, Dibrugarh University

Dibrugarh University




How to Cite

Paul, R., Gaftandzhieva, S., Kausar, S., Hussain, S., Doneva, R., & Baruah, A. (2020). Exploring Student Academic Performance Using Data Mining Tools. International Journal of Emerging Technologies in Learning (iJET), 15(08), pp. 195–209. https://doi.org/10.3991/ijet.v15i08.12557