A Learning
This paper reviews the current research status of expression recognition and affective computing in education, and analyzes the technical basis required to realizeective computing in the online learning environment from facial expressionrecognition, image pre-processing and featureextraction.
Abstract
. The development of technology informatization and intelligence makes personalized adaptive learning possible, especially the rapid development of artificial intelligence provides practical technical support for intelligent teaching. This paper reviews the current research status of expression recognition and affectivecomputingintheeducationfield,andanalyzesthetechnicalbasisrequired torealizeaffectivecomputingintheonlinelearningenvironmentfromfacial expressionrecognition,imagepre-processingandfeatureextraction,andexplores thetechnicalfeasibilityofthelearninganalysismodelbasedonaffectivecomput-ingisdiscussed.Throughaquestionnairesurvey,weinvestigatedlearners’accep- tanceofexpressionrecognitionandaffectivecomputingappliedtothefieldofedu-cationandteaching,andfoundthatmostlearnerswerewillingtouseAI-related technologiestocollectinformationwhenlearninginordertoimprovetheeffi-ciencyoflearning,andsomelearnerswereevenwillingtosharethisinformation withteachers.