Using a Fuzzy Logic-Based Emotional Intelligence Framework for Testing Satisfaction of Faculty in an Outcomes-Based Educational System
SPooja Pathak1, Vijay Kumar Dwivedi2
1Pooja Pathak*, Mathematics, IAH, GLA University, Mathura U.P. India.
2Vijay Kumar Dwivedi, Mechanical Department, IET GLA University, Mathura U.P. India.
Manuscript received on October 15, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 826-831 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4328119119/2019©BEIESP | DOI: 10.35940/ijitee.A4328.119119
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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: Workplace distress, a common manifestation in different profession has been seen in all over the world. Occupation pressure among faculty has been documented to impact job satisfaction and job performance, thereby undermining student teacher relationship leads to the future of student at risk. The purpose of this study to get satisfaction index of faculty in an outcome based education system by using fuzzy based emotional intelligence (EI). Emotional expression is essential for survival. One can give his emotional expression in language (linguistic) only. As per literature the fuzzy logic is much more capable to handle linguistic variable in uncertain environment. Therefore, to analyze the satisfaction index of faculty fuzzy logic is used. Research findings indicate that emotional literacy plays an important role in thinking, learning, exhaustion, depersonalization and a sense of low personal adjustment that can occur among individuals who work with other people in some capacity in a University. In this study, 450 faculty satisfaction data are taken and analyzed, needing further investigation more data and more comparative analysis. Fuzzy based emotional intelligence was not as distinctive as previous literature has indicated.
Keywords: Emotional Intelligence, fuzzy logic, linguistic variable, Satisfaction Index
Scope of the Article: fuzzy logic