Multi-dimensional dynamic evaluation of MOOC English mixed teaching based on BP neural network Online publication date: Wed, 19-Jul-2023
by Mian Wang
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 33, No. 4/5, 2023
Abstract: In order to overcome the problem of low accuracy in current evaluation methods of MOOC English mixed teaching, this paper proposes a multi-dimensional dynamic evaluation method based on BP neural network. By collecting evaluation data from teaching experts, teachers and students, the basic dataset of English teaching evaluation is constructed. The data from the evaluation basic dataset were taken as input samples, and the input samples were normalised. The input samples were input into the constructed BP neural network evaluation model, and the multi-dimensional dynamic evaluation results of MOOC mixed English teaching were output. Experimental results show that the evaluation accuracy of the proposed method is more than 90%, and the convergence can be achieved only about 50 times; the convergence speed is faster, and the evaluation time is shorter.
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