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Title: Analytics on talent search examination data

Authors: Anagha Vaidya; Vyankat Munde; Shailaja Shirwaikar

Addresses: Symbiosis International University, Pune, India ' Savitribai Phule Pune University, Pune, India ' Savitribai Phule Pune University, Pune, India

Abstract: Learning analytics and educational data mining has greatly supported the process of assessing and improving the quality of education. While learning analytics has a longer development cycle, educational data mining suffers from the inadequacy of data captured through learning processes. The data captured from examination process can be suitably extended to perform some descriptive and predictive analytics. This paper demonstrates the possibility of actionable analytics on the data collected from talent search examination process by adding to it some data pre-processing steps. The analytics provides some insight into the learner's characteristics and demonstrates how analytics on examination data can be a major support for bringing the quality in education field.

Keywords: learning analytics; educational data mining; EDM; clustering; linear modelling.

DOI: 10.1504/IJBIDM.2020.103844

International Journal of Business Intelligence and Data Mining, 2020 Vol.16 No.1, pp.20 - 32

Received: 06 Apr 2017
Accepted: 06 Jul 2017

Published online: 12 Nov 2019 *

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