Student Placement Prediction Model: A Data Mining Perspective for Outcome-Based Education System
Abhishek S. Rao1, Aruna Kumar S V2, Pranav Jogi3, Chinthan Bhat K4, Kuladeep Kumar B5, Prashanth Gouda6
1Abhishek S. Rao*, Dept. of Information Science & Engineering, NMAM Institute of Technology, Nitte, India.
2Aruna Kumar S V, Dept. of Information Science & Engineering, NMAM Institute of Technology, Nitte, India.
3Pranav Jogi, Dept. of Information Science & Engineering, NMAM Institute of Technology, Nitte, India.
4Chinthan Bhat K, Dept. of Information Science & Engineering, NMAM Institute of Technology, Nitte, India.
5Kuladeep Kumar B, Dept. of Information Science & Engineering, NMAM Institute of Technology, Nitte, India.
6Prashanth Gouda, Dept. of Information Science & Engineering, NMAM Institute of Technology, Nitte, India.
Manuscript received on 5 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 2497-2507 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4710098319/2019©BEIESP | DOI: 10.35940/ijrte.C4710.098319
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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: Campus placement plays a vital role in every educational institution in helping students to achieve their goals. Data mining classification can be used as a useful tool for extracting the associated information from the large scale student dataset. Data mining methods have been used broadly in the area of the education system which involves various methods and approach for discovering knowledge. In this paper, a predictive model is designed which can predict the category of placements (dream companies, super dream companies and mass recruiter companies) in which students are eligible by considering their past performance in academics and other curricular activities. The model will also suggest further skills required for future recruitments which may help the students for placement preparation. The paper also provides real-time experimental results and findings along with performance measures used for model validation which helps in achieving the milestone of outcome-based education (OBE) in educational institutes as it is given utmost importance in present scenario to ensure better placement prospects in students, which would in turn help the students for carrier building.
Keywords: Classification, Data Mining, Outcome-based education, Placement Prediction.
Scope of the Article: Classification