MOOC distance teaching effect evaluation method based on fuzzy entropy

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%.