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Interval Valued Intuitionistic Fuzzy Evaluations for Analysis of a Student’s Knowledge in University e-Learning Courses
Int. J. Fuzzy Log. Intell. Syst. 2018;18(3):190-195
Published online September 25, 2018
© 2018 Korean Institute of Intelligent Systems.

Taekyun Kim1, Evdokia Sotirova2, Anthony Shannon3, Vassia Atanassova4, Krassimir Atanassov2,4, and Lee-Chae Jang5

1Department of Mathematics, Kwangwoon University, Seoul, Korea
2Intelligent Systems Laboratory, University “Prof. Dr. Assen Zlatarov”, Burgas, Bulgaria
3Warrane College, The University of New South Wales, Kensington, Australia
4Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
5Graduate School of Education, Konkuk University, Seoul, Korea
Correspondence to: Lee-Chae Jang
(Lcjang@konkuk.ac.kr)
Received July 10, 2018; Revised September 22, 2018; Accepted September 22, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In the paper a method is proposed for evaluation of the students’ knowledge obtained in the university e-learning courses and an evaluation of the whole student class. For the assessment of the student’s solution of the respective assessment units the theory of intuitionistic fuzzy sets is used, while for the class evaluation, interval valued intuitionistic fuzzy sets is used. The obtained intuitionistic fuzzy estimations reflect the degree of each student’s good or poor performances, for each assessment unit. The interval valued intuitionistic fuzzy evaluations are based on the separate student’s evaluations. We also consider a degree of uncertainty that represents such cases wherein the student is currently unable to solve the problem. The method presented here provides the possibility for the algorithmization of the process of forming the student’s evaluations.
Keywords : e-learning, Interval valued intuitionistic fuzzy evaluations, Intuitionistic fuzzy evaluation, Model