Decision support in providing personalized services using emotional artificial intelligence
Abstract and keywords
Abstract (English):
An approach to personalized service rendering based on using affective computing technologies is described. The proposed approach consists of considering clients’ emotional states and their individual characteristics in the process of providing services. Rendering services is supplemented by the formalization stages of the client’s emotional state and emotional support. The paper considers online learning as the subject area of research. A general description of the online learning process is given. It is concluded that there is no correction of the learners’ emotional state during the lesson. The dependence of the learners’ knowledge level on their emotional state is revealed. A review of existing approaches to considering learners’ emotional states in the process of online learning is given. Learners’ specific behaviour during the lesson is analysed. The features of academic emotions are also considered. The objective is set to increase the online learning effectiveness by taking into account learners’ emotional states and their individual characteristics and by providing emotional support in the learning process. An approach is proposed to formalise learners’ emotional states based on using facial muscle movements as a universal way of recognizing emotions. The stages of recognizing learners’ emotions during the lesson are also described in detail. The task is set to select emotional support based on the learners’ classification according to their emotional state and their individual characteristics using the nearest neighbour method.

personalized services, affective computing, learners’ emotion recognition, online learning, facial expression recognition, classification, nearest neighbour method
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