Research on teaching quality evaluation method of network course based on intelligent learning
by Hailong Tang
International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL), Vol. 30, No. 4, 2020

Abstract: In view of the problems of poor evaluation effect and high evaluation delay in the existing evaluation methods for network course teaching quality, this paper designs an evaluation method based on intelligent learning. The design idea is as follows: with the help of public services, different forms of teaching tasks are summarised and data reduction is processed. On this basis, the restricted Boltzmann machine method based on intelligent learning is adopted to design the evaluation algorithm, and the teaching quality is evaluated with weighting parameters and preference parameters. Through the application part, different application functions such as information query, scene construction, data management and view viewing during the network course teaching are realised. The experimental results show that this method has high evaluation efficiency, short evaluation delay, and significantly reduced actual use of class time, which guarantees the teaching quality of teachers and the overall learning effect of students, and has high application advantages.

Online publication date: Sun, 01-Nov-2020

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