Intuitionistic fuzzy evaluations for analysis of a student's knowledge of mathematics in university e-learning courses

Author(s):  
Evdokia Sotirova ◽  
Krassimir Atanassov ◽  
Anthony Shannon ◽  
Taekyun Kim ◽  
Maciej Krawczak ◽  
...  
2018 ◽  
Vol 18 (3) ◽  
pp. 190-195 ◽  
Author(s):  
Taekyun Kim ◽  
Evdokia Sotirova ◽  
Anthony Shannon ◽  
Vassia Atanassova ◽  
Krassimir Atanassov ◽  
...  

2016 ◽  
Vol 5 (3) ◽  
pp. 14-29 ◽  
Author(s):  
Mukta Goyal ◽  
Alka Tripathi ◽  
Divakar Yadav

Learner's performance evaluation in an E-learning environment is a multi-criteria decision problem and important to personalize the sequence of learning concepts according to their knowledge level. Crisp responses, leads uncertainty in the evaluation process due to successful guesses or choosing a more probable answer. Analysis of learner's response to a complex/subjective questions needs more effort. Moreover, due to uncertainty and imprecise nature of learner, traditional methods are inadequate to assess, how much time he has spent on studying the learning contents and also the number of backtracking he followed. This paper proposes an intuitionistic fuzzy multicriteria decision making that investigates the use of an intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS method) for the evaluation of student in an E-learning environment. Synthetic data are created for the criteria's that affect the student evaluation in E-learning domain and thereafter results are evaluated.


Author(s):  
A. Shannon ◽  
E. Sotirova ◽  
K. Atanassov ◽  
M. Krawczak ◽  
P. Melo-Pinto ◽  
...  

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