金雅倫

Collaborative problems solving (CPS) skills are indispensable ability for modern citizens. Due to physical and mental characteristics, students with disabilities generally have low empathy, limited cognition, and slow and insufficient development of social interaction skills, which makes it difficult to initiate dialogue with others, maintain and understand interactions with others, and therefore it is difficult to develop meaningful social relationships. It also causes insufficient ability for CPS skills.

Data Science and artificial intelligence are booming, and are widely used in many fields with considerable results, and they have also promoted intelligent thinking. According to the method of data science, the digital learning is intelligentized, and deeper analysis and decision-making are carried out to give students more immediate and appropriate guidance and support. This is the current trend of digital learning. Due to the high heterogeneity of physically and mentally handicapped students, it is even more necessary to provide appropriate learning guidance in response to individualized differences.

This research reference the data science concept, designing a CPS Ability Learning Tutoring Model, using machine learning technology to develop learning monitoring, ability analysis, decision-making, tutoring and optimization mechanisms, and developing a Digital Game-Based Learning Tutoring Platform, to provide appropriate guidance and improve learning effectiveness. Finally, this experiment is to verify its effectiveness and feasibility of this CPS Ability Learning Tutoring Model.