DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW | Zendy

Pragati Sharma | Zendy; Sanjiv Sharma | Zendy

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DATA MINING TECHNIQUES FOR EDUCATIONAL DATA: A REVIEW

Author(s) -

Pragati Sharma,

Sanjiv Sharma

Publication year - 2020

Publication title -

international journal of engineering technologies and management research

Language(s) - English

Resource type - Journals

ISSN - 2454-1907

DOI - 10.29121/ijetmr.v5.i2.2018.641

Subject(s) - educational data mining , computer science , data mining , cluster analysis , data science , field (mathematics) , popularity , knowledge extraction , data stream mining , set (abstract data type) , data set , information retrieval , machine learning , artificial intelligence , psychology , social psychology , mathematics , pure mathematics , programming language

Recently, data mining is gaining more popularity among researcher. Data mining provides various techniques and methods for analysing data produced by various applications of different domain. Similarly, Educational mining is providing a way for analyzing educational data set. Educational mining concerns with developing methods for discovering knowledge from data that come from educational field and it helps to extract the hidden patterns and to discover new knowledge from large educational databases with the use of data mining techniques and tools. Extracted knowledge from educational mining can be used for decision making in higher educational institutions. This paper is based on literature review of different data mining techniques along with certain algorithms like classification, clustering etc. This paper represents the effectiveness of mining techniques with educational data set for higher education institutions.

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