The analysis of artificial intelligence-based mobile learning in students' open teaching recommendation system based...

This exploration aims to improve the time use efficiency of students in the process of mobile learning and the learning effect of students in the process of open teaching. First, the details and current situation of mobile learning and open teaching mode are analyzed. Then, the artificial intelligence (AI) deep learning (DL) recommendation system is proposed. Finally, the application model of the AI DL recommendation system is designed based on mobile learning. The results show that the students use mobile learning more frequently. The two groups of students are investigated on the status of AI mobile learning. It is found that about 85% of middle school students use AI mobile platform for learning in a week. However, the number of people is relatively small on Saturday and Sunday, and the proportion of people is generally about 70%. Moreover, the two groups of students use their mobile phones most during their studies. Then, in the survey of students' acceptance of the AI DL recommendation system in mobile learning, it is found that the DL recommendation system has a high number of recommendation times and acceptance times in the daily learning process. Finally, the satisfaction of the designed DL recommendation system is generally the highest at about 83% and the lowest at about 75%. Decision Tree (DT) recommendation system satisfaction is about 70% at most and about 50% at least. This exploration provides technology to promote mobile learning and contributes to the development of an open teaching mode.