Not personalized

The lack of AI analysis capabilities in traditional online education platforms directly leads to defects in personalized teaching. Firstly, the standardization of course content and teaching resources makes it difficult for platforms to meet students' personalized needs. This is because online education platforms often provide fixed course schedules and materials, ignoring differences in students' interests, abilities, and learning speed. Moreover, this one-size-fits-all teaching method is difficult to arouse students' interest in learning, thereby reducing learning effectiveness.

Secondly, traditional online education platforms lack real-time tracking of students' learning progress and feedback. In a large-scale online education environment, teachers find it difficult to monitor the learning status of each student in real-time, thus being unable to provide targeted help. This can lead to students not receiving timely support when facing difficulties, thereby affecting their learning effectiveness. In addition, due to the lack of personalized feedback, students cannot clearly understand their strengths and weaknesses in the course, making it difficult for them to find ways to improve. Finally, traditional online education platforms are unable to provide students with personalized learning paths. Due to the fixed nature of course settings and teaching resources, it is difficult for students to adjust their learning according to their needs. In this case, students may face problems of being overwhelmed or underwhelmed with their learning tasks, which can lead to an imbalance in learning pressure and effectiveness.