Abstract
to better carry out Massive Open Online Courses (MOOC) teaching evaluation and improve teaching effect, firstly, a teaching decision support system with evaluation function is designed by analyzing the actual situation of the college. Secondly, the decision tree data mining algorithm is introduced in the subsystem of student score analysis and evaluation. Finally, the decision tree model of student score analysis evaluation is constructed according to the decision tree algorithm. Through the practical exploration of applying the decision tree algorithm to the MOOC teaching evaluation management system of higher vocational colleges, it is found that the application of data mining technology to the construction of digital campus is not only reflected in the theoretical feasibility, but also reflected in its technical feasibility.
Highlights
As a new teaching method that has developed rapidly in recent years, online teaching technology has been widely welcomed by society and colleges
Building a more objective and comprehensive intelligent decision support system for online teaching has become the focus of current thinking
Return to the most common class N in S as the leaf node; step 5: in S, select the attribute t with the highest information gain, and mark the node as t; step 6: for each known value ai in each t, a branch with a condition of t is generated by the node N; step 7: set Si as the sample set in S, and judge whether Si is null
Summary
As a new teaching method that has developed rapidly in recent years, online teaching technology has been widely welcomed by society and colleges. Online teaching has abundant education resources and provides learners with various kinds of knowledge information with rich and colorful pictures and texts. Different from traditional teaching, with the increasing abundance of online teaching resources, it is more and more difficult for online learners to obtain objective learning scores. Building a more objective and comprehensive intelligent decision support system for online teaching has become the focus of current thinking. In this regard, based on the understanding of learners’ e-learning behavior, MOOC learning behavior analysis and intelligent decision support system for teachiJET ‒ Vol 14, No 12, 2019. It is hoped that the construction of this system will provide more favorable references for the current large number of online teaching systems, so as to provide references for the adjustment and improvement of online teaching systems, so as to further improve the effect of online teaching
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