MOOC distance teaching effect evaluation method based on fuzzy entropy Online publication date: Fri, 01-Mar-2024
by Qingqin Chen
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 34, No. 2/3, 2024
Abstract: In order to overcome the problems of low evaluation accuracy and long evaluation time in traditional evaluation methods, a MOOC distance teaching effect evaluation method based on fuzzy entropy is proposed. Firstly, we mine the MOOC distance learning data. Secondly, according to the needs of teaching effect evaluation, we build the MOOC distance teaching effect evaluation index system. Finally, according to the principle of fuzzy entropy, the fuzzy entropy weight of the evaluation index is calculated, the fuzzy entropy weight is normalised, and the attribute matrix of the evaluation index is constructed. The ideal point and closeness degree are calculated according to the attribute matrix, and the effect of MOOC distance teaching is evaluated through the closeness degree. The experimental results show that compared with the traditional evaluation methods, this method greatly improves the evaluation accuracy on the basis of reducing the evaluation time, and the maximum evaluation accuracy is 97%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook