杜仲弘

The purpose of this study was to design a “smart agent model” that monitors, predicts behavior, conducts behavioral analysis, makes decisions, provides counseling, and learns through data science methods. Then, according to the model, a smart social interaction learning coaching agent is developed and applied to social interaction learning of special education students. Finally, the game-based social skills learning platform is used to verify the feasibility of special education digital learning smart agents and the effectiveness of learning and consulting agents on the social interaction ability of students with disabilities. The study arranged for 12 students from the Tainan City Elementary School to the fifth-grade resource class for disabilities to conduct experiments. Through the visual analysis method and simplified time series C statistics, the trend of the positive and negative behavior frequency of students during the game period is analyzed, and the progress of the disciplines in various social skill projects is discussed. The experimental results showed that the subject's problem behavior frequency decreased significantly and the trend of positive behavior increased. Students' computer skills can be improved through the student's game action footprint and game movement footprint. As the number of experiments increases, students help others or seek help from others by listening to the system prompts progress to actively interacting with others and cooperating to solve problems. The above situation indicates that the growth trend of students' social skills proves that this learning platform has positive benefits for social skills learning.