The invention discloses a learning emotion state recognition method based on multi-source information fusion. The learning emotion state recognition method based on the multi-source information fusionincludes the steps that facial expression images and interaction behavior data of learners are collected from an online learning platform, serial expression images within a certain time period are obtained according to an expression recognition algorithm, and then features are extracted and then classified; useful interaction behavior data pieces are extracted from a Web log file, and a subjective Bayes method is adopted to conduct uncertainty inference and deep data analysis. On the basis of judging concern degrees of the learners on current learning content, in combination with expression recognition results, online learning emotion states of the learners are judged are classified into a satisfaction state, a confusion state and the like. The learning emotion state recognition method based on the multi-source information fusion is applicable to teaching in disciplines which implement hybrid learning; through expression recognition, the online learning emotion states of the learnersare grasped, so that manual intervention is provided more specifically. According emotion recognition results, grasping conditions and interest of the learners on the current learning content can alsobe judged.
Learning emotion state recognition method based on multi-source information fusion