Performance Evaluating System Based on MapReduce in Context of Educational Big Data

Performance Evaluating System Based on MapReduce in Context of Educational Big Data

Chitresh Verma, Rajiv Pandey, Devesh Katiyar
DOI: 10.4018/IJOCI.2018010101
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Abstract

The Big Data subsist in every characteristic of our daily life. The educational Big Data is one of these aspects of Big Data which is linked to student life. This article provides the comprehensive understanding of the implementation of the grade analysis system using educational Big Data. The grade analysis can be used for helping the students in many ways like selecting an elective subject, determining the toughness of elective subjects. Selection of good subject by the student will improve their career opportunities and placement probability. Further, this article builds a reference performance evaluating system for any future performance system with other aspects like employee performance evolution in any human capital management system(HCM).
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Many grading systems and studies had been developed over the last decades to help the student in improving their performance. One such system is the literature based learning and performance system which measured along its analysis was developed (Muñiz-Swicegood, 1994). It involved the testing the learning capabilities of students consisting of bilingual and monolingual. The experiment mainly focused on learning of students speaking Spanish and English language. The findings were published in Bilingual Research Journal, 1994 and involved results of the examination of metacognitive instructions learning.

One another grade analysis system involved admission test marks and grade point average (GPA) and it tried to predict performance of the student in Pharmacy College to help the pharmacy colleges and license examiner. (Kuncel, Credé, Thomas et al., 2005) The experiment used the Hunter and Schmidt psychometric meta-analytic method. It had applied the method of comparison of admission test marks and GPA.

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