The application of curriculum recommendation algorithm in the driving mechanism of industry–teaching integration in colleges and universities under the background of education reform

Abstract

At present, there is a poor connection between theory and practice in the driving mechanism of industry–teaching integration in colleges and universities. And with the increasing courses, the recommendation accuracy of the recommendation algorithm has also decreased. Therefore, the research built a teaching platform of the Internet of Things (IoT) based on the integration of industry and education and improved its internal online education course recommendation algorithm. Meanwhile, experiments verified its performance. The experimental results show that the response time of several important interfaces is maintained between 0 and 300 ms. In the verification experiment of the improved algorithm for building the rule engine, when the rules are 50, the traditional Rete algorithm takes the most time. In terms of total time consumption, the traditional Rete algorithm takes more time than the improved Rete algorithm. The mean absolute error of the User-Characteristics and Interest Clustering (CCIC) algorithm is 0.8116, the root mean square error is 0.9455, the accuracy is 0.3043, and the recall is 0.1475, which are better than the comparison algorithms. In the recommendation of actual agricultural courses, the overall satisfaction of the User-CCIC algorithm is more than 70%, with good prediction accuracy. In general, the IoT education platform based on the combination of industry and education established by this research has better application prospects, and the User-CCIC algorithm recommended by this research has a good practical effect in actual course recommendation.

Keywords

• educational reform
• course recommendation algorithm
• dynamic mechanism of industry–education integration
• collaborative filtering