A Review on Student Performance Analysis Based on Result Outcome

Authors(4) :-Rajat Kumar Gupta, Rohan Bhatnagar, Sanyam Jain, Dr. Avdhesh Gupta

In our daily academic life we see a lot of data gets accumulated as a result of processes like examinations,registration,event organisation etc in schools and colleges. This data can be used effectively for the beneficiary of the institution itself. As this data is only operational ,we can develop a system for a graduation or higher level institution which will help the administration gain information turned knowledge from accumulated data. The system can be developed to perform three main functions :student performance analysis, prediction of rank of a student & evaluating the teaching quality. The system will take input from the faculty in the form of marks into it's database, analyse the students marks using neural networks, training & optimize data. The knowledge is hidden among the educational data set and it is extractable through data mining techniques. Present paper is designed to justify the capabilities of data mining techniques in context of higher education by offering a data mining model for higher education system in the university. In this research, the classification task is used to evaluate student’s performance and as there are many approaches that are used for data classification, the decision tree method is used here. By this task we extract knowledge that describes students’ performance in end semester examination. It helps earlier in identifying the dropouts and students who need special attention and allow the teacher to provide appropriate advising/counselling.

Authors and Affiliations

Rajat Kumar Gupta
Computer Science and Engineering Department, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
Rohan Bhatnagar
Computer Science and Engineering Department, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
Sanyam Jain
Computer Science and Engineering Department, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
Dr. Avdhesh Gupta
Computer Science and Engineering Department, IMS Engineering College, Ghaziabad, Uttar Pradesh, India

KDD, FES, CSL, E-Ectively, Data Mining

  1. B. Kitchenham, R. Pretorius, D. Budgen, O. Pearl Brereton, M. Turner, M. Niazi, S. Linkman, Systematic literature reviews in software engineering - a tertiary study, Inf. Softw. Technol. 52 (8) (2010) 792–805. doi:10.1016/j.infsof.2010.03.006. URL http://dx.doi.org/10.1016/j.infsof.2010.03.006
  2. Data Mining Curriculum". ACM SIGKDD. 2006-04-30. Retrieved 2014-01-27. http://www.kdd.org/curriculum/index.html
  3. http://www.kdd.org/curriculum/index.html
  4. Fayyad, Usama; Piatetsky-Shapiro, Gregory; Smyth, Padhraic (1996). "From Data From From Data Mining to knowledge Discovery in Databases "(PDF) http://www.kdnuggets.com/gpspubs/aimag-kdd-overview-1996-Fayyad.pdf
  5. http://www2.cs.uregina.ca/~dbd/cs831/notes/kdd/1_kdd.html
  6. Juan Zhang, Changjun Zhu (2009) p 33-35“GA-based Neural Network model for Teaching Evaluation”. 2nd International Conference on Power Electronics and Intelligent Transportation System.
  7. GB-Zadok et al., 2007; Thai-Nghe, 2010A
  8. M. Bray, The shadow education system: private tutoring and its implications for planners, (2nd ed.), UNESCO, PARIS, France, 2007.
  9. U. bin Mat, N. Buniyamin, P. M. Arsad, R. Kassim, An overview of using academic analytics to predict and improve students’ achievement: A proposed proactive intelligent intervention, in: Engineering Education (ICEED), 2013 IEEE 5th Conference on, IEEE, 2013, pp. 126–130.

Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 2017-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 168-171
Manuscript Number : CSEIT172310
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Rajat Kumar Gupta, Rohan Bhatnagar, Sanyam Jain, Dr. Avdhesh Gupta, "A Review on Student Performance Analysis Based on Result Outcome", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.168-171, May-June.2017
URL : http://ijsrcseit.com/CSEIT172310

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