Systematic Review of Predicting Student’s Performance in Academics
Mukesh Kumar1, Yass Khudheir Salal2
1Mr. Mukesh Kumar, Assistant Professor, Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India.
2Mr. Yass Khudheir Salal, Department of System Programming, South Ural State University (National Research University) (Chelyabinsk, Russian Federation).
Manuscript received on 18 February 2019 | Revised Manuscript received on 27 February 2019 | Manuscript published on 28 February 2019 | PP: 54-61 | Volume-8 Issue-3, February 2019 | Retrieval Number: C5689028319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data mining (DM) gaining popularity due to its advantages in the educational environment. Most of the educational institution, now a day applied these techniques to make improvement in their education system. By using these techniques, academic performance of the student is analyzed and if find anything wrong with the student performance then timely help will be provided to that student. In our education system, we lack in finding those factor which mostly affects the student performance in academics. Therefore, a systematic review of all the authors work done in this field is required to understand the data mining application in education and how it helps to improve and predict the student academic performance. In this article, the main focus moves around two important factors: Firstly, to find the most critical factors which affect the student performance used by the most researcher and secondly to find the algorithm which is mostly used
Keywords: Academic Performance, Educational Data Mining, Prediction, Classification.
Scope of the Article: Classification