Analyzing Student Performance Using Data Mining

  • Pankhurhi MallikEmail author
  • Chandrima Roy
  • Ekansh Maheshwari
  • Manjusha Pandey
  • Siddharth Rautray
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 904)


Analysis of student performance will help us understand the various factors that affect the overall of a student. Big Data Environment helps in analyzing the various concepts which are inbuilt for better strategies and the choices that are taken for an organization’s overall development. Reduction in cost, time, the development of optimized and novice products, efficient and smart decision-making are some of the fields where it proves to be useful. Considering, the Higher Education System, which is inculpated in predicting the performance of students, this work will help various institutions in not only enhancing the quality of education, but also upgrading the overall accomplishments, identifying the pupil’s at risk, and thereby refining the education resource management. This introspection will aid in identifying the patterns, where a comparative study between two distinct methods has been made in order to predict the student’s success and a database has been generated.


Data mining Student performance analysis Clustering K means Mean shift 


  1. 1.
  2. 2.
    Oyelade, O.J., Oladipupo, O.O., Obagbuwa, I.C.: Application of K means clustering algorithm for prediction of student’s academic performance. J.-Int. J. Comput. Sci. Inf. Secur.Google Scholar
  3. 3.
  4. 4.
    Roy, C., Rautaray, S.S., Pandey, M.: Big data optimization techniques: a survey. Int. J. Inf. Eng. Electron. Bus. (IJIEEB) 10(4):41–48 (2018).
  5. 5.
    Osmanbegovic, E., Suljić, M.: Data mining approach for predicting student performance. Econom. Rev. J. Econom. Bus. X(1) (2012)Google Scholar
  6. 6.
    Kekane, S., Khairnar, D., Patil, R., Vispute, S.R., Gawande, N.: Automatic student performance analysis and automatic student performance analysis and monitoring monitoring. Int. J. Innovative Res. Comput. Commun. Eng. (2017)Google Scholar
  7. 7.
    Priya, I.U.: Predicting academic performance of students using data mining techniqueGoogle Scholar
  8. 8.
    Sa, C.L.: Dayang Hanani bt. Abang Ibrahim, Emmy Dahliana Hossain, Mohammad bin Hossin “Student Performance Analysis System (SPAS)”Google Scholar
  9. 9.
    Ramesh, V., Parkavi, P., Ramar, K.: Published a paper titled “Predicting Student Performance- A Statistical and Data Mining Approach. Int. J. Comput. Appl. (2013)Google Scholar
  10. 10.
    Suryadarma, D., Suryahadi, A., Sumarto, S., Rogers, F.H.: Improving student performance in public primary schools in developing countries: evidence from Indonesia. Available from
  11. 11.
    Chemers, M.M., Hu, L., Garcia, B.F.: Academic self-efficacy and first-year college student performance and adjustment. Am. Psychol. Assoc.Google Scholar
  12. 12.
    García, Á.B.: Student Data SetGoogle Scholar
  13. 13.
    Das, N., et al.: Big data analytics for medical applications (2018)Google Scholar
  14. 14.
    Roy, C., Pandey, M., Rautaray, S.S.: A proposal for optimization of horizontal scaling in big data environment. Advances in Data and Information Sciences. Springer, Singapore, pp. 223–230 (2018)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Pankhurhi Mallik
    • 1
    Email author
  • Chandrima Roy
    • 1
  • Ekansh Maheshwari
    • 1
  • Manjusha Pandey
    • 1
  • Siddharth Rautray
    • 1
  1. 1.School of Computer EngineeringKalinga Institute of Industrial Technology (KIIT) Deemed to Be UniversityBhubaneswarIndia

Personalised recommendations