Fuzzy similarity measures as a basis for the selection of examiners

Abstract

Examinee and examiner plays a pivotal role in educational grading system. Perception of experts in evaluating student's answer script is of vital significance. Multiple experts evaluating students' academic performance involves epistemic uncertainty which can be modelled using fuzzy set theory. How many evaluators/experts are almost similar in their perceptual subjective evaluation of the students answer paper? In other words, how many experts are reliable for a particular evaluation task with defined possibility level? The paper addresses the issue of the selection of similar examiners using fuzzy relational calculus. The case study reveals that all twenty evaluators agree to one another considering the similarity measures on fuzzy sets. The computed Fleiss Kappa coefficient is 0.74 which signifies excellent agreement between all the twenty experts.

Development Of An E-Learning Model Using CMS Moodle During Covid 19

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