The Intelligent Guided Learning System represents a powerful synergy between artificial intelligence and education, enabling each to enhance the other. It offers an effective solution for large-scale personalized learning by precisely reducing student workload while boosting learning efficiency. This system plays a key role in advancing the digital transformation and intelligent modernization of education.

Centering on the three core components of the learning process—context, learner, and service—the research covers disturbance-free sensing and intelligent recognition of learning environments, cognitive tracking and attribution analysis of learners, and dynamic customization and precise adaptation of learning services. The goal is to develop a technical framework where learning scenarios are computable, learners are well understood, and learning services are fully adaptable. This framework underpins the construction of the intelligent guided learning system and supports rigorous validation of its effectiveness in practice.

Key Technologies and Achievements:

Intelligent Perception Technology: 2 authorized domestic invention patents, 2 pending patents, and 2 SCI journal articles published.

Deep Cognitive Tracking Technology: 3 authorized domestic invention patents, 2 pending patents, 3 SCI journal articles, and 1 CCF T1-level paper published.

Intelligent Recommendation Technology: 2 pending patents and 3 SCI journal articles published.