Artificial intelligence in the field of education presents both promising prospects and significant challenges in advancing research on learning engagement. By utilizing multimodal integration and multidimensional modeling, AI has the potential to enhance the recognition of learning states, providing more personalized and adaptive interventions for students. However, several challenges remain, including the complexity of integrating diverse data sources, maintaining ethical balance in intervention strategies, and addressing the lack of explainability in AI models. To overcome these challenges, future development should focus on creating a collaborative framework that integrates technology, education, and ethics, optimizing AI systems, ensuring transparency in decision-making processes, and fostering a balance between technological innovation and core values of education, ultimately creating a sustainable and effective AI-driven learning ecosystem.