Assessment of E-learning System in Higher Education Based on Hesitant Fuzzy Information with Incomplete Attribute Weights

Hong Ye

Abstract


With the development of information technology, colleges and universities around the world are constructing E-learning system to meet their students' and faculty's needs. E-learning can effectively help students to learn varieties of knowledge and even skills they want to obtain.
Therefore, the efficiency of E-learning system is important to popularize and develop it. Then, in this paper, we investigate to propose a method to evaluate E-learning system in higher education based on some criteria. Hereinto, this assessment problem can be considered as a multiple attribute decision making (MADM) problem. Thus, TOPSIS method, as a popular multiple attribute decision making method, is introduced in this paper to solve this assessment problem. In MADM problem, how to acquire preference of the decision maker is critical. In order to solve this issue, hesitant fuzzy set is developed in this paper. Weight vector, as a balance to weight the importance of different attributes, is hard to obtain. Then, a new fuzzy weight method is proposed to determine attribute weights. Finally, a case study is demonstrated to verify the applicability of this method.

Keywords


E-learning system; hesitant fuzzy set; higher education; multiple attribute decision making; TOPSIS

Full Text:

PDF


Copyright (c) 2017 Hong Ye


International Journal of Emerging Technologies in Learning. ISSN: 1863-0383
Creative Commons License SPARC Europe Seal
Indexing:
Web of Science ESCI logo Engineering Information logo INSPEC logo DBLP logo ELSEVIER Scopus logo EDiTLib logo EBSCO logo Ulrich's logo Google Scholar logo Microsoft® Academic Search