Application Effect Robust Evaluation Algorithm of Online and Offline Hybrid Teaching Mode in Undergraduate Colleges

In order to improve the practical application effect of the mixed teaching mode, an application effect evaluation algorithm of online and offline hybrid teaching mode in undergraduate colleges is proposed. Firstly, the big data technology is used to collect the big data in the online and offline mixed teaching process of undergraduate colleges, and an evaluation index system is built from three dimensions to extract the required data according to the indicators. Then the association rules between the relevant data of the evaluation indicators are established to obtain the phase space distribution of the data. Finally, the constraint parameter analysis method is used to fuse the control variables and explanatory variables of the index related data to realize the online and offline mixed teaching effect evaluation. The experimental results show that the proposed algorithm achieves an ideal evaluation result of online and offline mixed teaching effect, which is conducive to improving the teaching quality.