The Personalized Learning Path of Affective Computing in Enhancing Emotional Identification with Chinese Culture among International Students Studying in China

Traditional measurements of emotional identification with Chinese culture among international students studying in China focus on quantifiable individual factors, while artificial intelligence technology and affective computing expand the scope to non-quantifiable individual factors such as facial expressions, language, and body language. Based on personalized learning theory, OCC theory, and cultural adaptation theory, the application of affective computation in enhancing international students' emotional identification with Chinese culture can be approached from the three aspects of "personality + emotion + cultural adaptation". On the personalized level, affective computation using full-sample, whole-process, multimodal data in learning scenarios is employed to depict the personalized feature emotional portrait of implicit emotions of international students studying in China. By utilizing artificial intelligence technology, natural language processing technology, and adaptive learning technology, analyze and compute the emotions embedded in the non-quantitative individual factors during human-computer interaction. Furthermore, based on predicting the different stages of cultural adaptation of international students in China, customize personalized and precise learning programs to enhance emotional identification by pinpointing the emotional preferences and weaknesses of international students in China. Based on affective computation of artificial intelligence technology, a closed loop of affective computation is achieved through stages such as collection-recognition-computation-portrayal-analysis-positioning-recommendation, effectively enhancing international students' emotional identification with Chinese culture.