This chapter synthesizes the results of several references and discussions, discussing the methods to improve students’ learning effects and experience through online teaching interactive systems and learning effect evaluation algorithms. After summarizing the existing literature, it has been found that online education has become an important teaching mode in the current information age. Previous research shows that online teaching not only provides students with a flexible and convenient learning platform but also provides teachers with opportunities to guide students in real time, thus achieving good teaching results. However, the existing research often ignores the importance of scientifically evaluating the learning effect of online teaching systems, which leads to the inability to objectively evaluate students’ learning achievements. Therefore, this chapter aims to fill this research gap. By designing an online teaching interactive system and adopting an algorithm based on deep learning to evaluate students’ learning situation, a more accurate and scientific evaluation of the learning effect can be achieved. The results show that the algorithm in this chapter has a certain effect on curriculum evaluation, and the accuracy rate can reach 95.9%, which provides important theoretical support and technical means for improving students’ learning effect and experience.