The project focuses on the three key elements of learning—learning environments, learners, and educational resources/services—and how they interact dynamically. It explores important technologies for data-driven personalized learning and intelligent educational services. Specifically, the research looks at how to perceive learning processes in integrated multi-space environments; analyze and model learners using data from multiple sources; develop theories and methods for personalized learning plans based on knowledge structures; create intelligent guidance for diverse learning resources; and design intelligent learning companion systems based on embodied cognition, including testing their practical use.

        Breakthroughs in these core theories and technologies will help design effective multi-space educational settings, deepen our understanding of learner behavior and thinking, and enable more accurate and personalized intelligent learning services.