A Framework and Environment Design of Human-Machine Cooperations in Junior Science Education

Human-Machine-Environment (HME) Tri-Co (Coexisting, Cooperative, Cognitive) Education is an indispensable prerequisite and main content of Artificial Intelligence empowering junior science education. Moreover, it is also a critical requirement for improving the quality of education and promoting the high-end development of education information. Building a unique learning environment with scene perception and the intelligent cognitive process is a tremendous challenge for diverse needs in junior scientific learning scenarios. Therefore, it is necessary to design advanced human-computer interaction scenarios and functions. This paper aims to tackle the critical scientific problem of this field for HME Tri-Coeducation, i.e., HME multimodal real-time scene perception and Tri-Co collaborative analysis via Multi-source data, fundamental theories, application method, and verification system, and to build HME Tri-Coeducation environment in “Perception-Analysis-Interaction” architecture. For the requirements of an education environment empowered by artificial intelligence, this paper will also study critical technologies of human-machine cooperative and education environment building driven by big data. It is significant to promote the cross-integration of multi-disciplines such as pedagogy, intelligent technology, and cognitive science.