This paper proposes a new image recognition model based on deep learning. By improving the convolutional neural network architecture, the image recognition accuracy in complex scenarios is significantly improved. Experimental results show that the model performs better than existing methods on multiple public datasets.

This study explores the application of educational data mining technology in learning analysis and proposes a learning effect prediction model based on student behavior data. Through the analysis of large-scale online course data, the effectiveness of the model in predicting student academic performance and dropout risks was verified.

This paper discusses the current application status and future development trends of artificial intelligence technology in the field of education, and analyzes the design principles and technical challenges of AI education applications such as intelligent tutoring systems and adaptive learning platforms. The research proposes an interdisciplinary AI education research framework that provides theoretical guidance for future research.