A Survey on Educational Data Mining-Prediction and Classification
Ashna Sethi1, Charanjit Singh2
1Ashna Sethi, Department of Computer Science and Engineering, Regional Institute of Management and Technology, Mandi Gobindgarh (Punjab), India.
2Charanjit Singh, Assistant Professor, Department of Computer Science and Engineering, Regional Institute of Management and Technology, Mandi Gobindgarh (Punjab), India.
Manuscript received on 15 April 2017 | Revised Manuscript received on 22 April 2017 | Manuscript Published on 30 April 2017 | PP: 14-18 | Volume-6 Issue-9, April 2017 | Retrieval Number: I2430046917/17©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Educational Data Mining (EDM) is an upcoming field examining and exploring data in educational context by implementing different Data Mining (DM) techniques/tools. It provides knowledge of teaching and learning as a process for effective education planning. In this survey work focuses on highlighting Techniques and educational Outcomes. In this paper, Various DM techniques are discussed and comparison of classifiers is made. A general Methodology for classification and Prediction is mentioned.
Keywords: Educational Data Mining (EDM), EDM Components, DM Methods, Education Planning.
Scope of the Article: Classification