ASSESSMENT OF THE POSSIBILITIES OF IMPLEMENTATION OF EMOTIONAL STATE RECOGNITION TECHNOLOGIES IN THE DISTANCE EDUCATION SYSTEM
Authors:   Kyiv National University of Construction and Architecture, Ukraine, Tereikovska Liudmyla , Tereikovskyi Ihor ,   National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine
Published: December 2023

One of the most promising directions in the development of distance learning systems is the use of technologies in them that allow to effectively organize the cognitive activity of students in an automatic mode for their assimilation of educational materials. For this, the current emotional state of the students should be taken into account, which indicates the expediency of introducing appropriate means of recognition into the distance learning system. The subject of the study are models, methods and means of recognizing the emotional state of members of the distance learning system by a person's face and voice. The purpose of the work is to determine the list of parameters for evaluating the effectiveness of means of recognizing the emotional state of members of the distance learning system. The research methodology is based on the theory of complex systems and system analysis and involves the determination of an approach to the development of technology for harmonizing the emotional state of a student of a higher educational institution, the analysis of scientific and practical works in the field of operational recognition of the face and emotional state of a user of a computer system based on the image of a face and voice, and as well as the definition of the list of parameters for evaluating the effectiveness of the relevant means of recognition. As a result of the conducted research, an approach to the development of a technology for harmonizing the emotional state of a student of a higher educational institution was determined, which involves a neural network analysis of the biometric parameters of a student of a distance learning system to recognize his current emotional state, which should be used to adjust the type and volume of educational materials when they are submitted in an automated mode. The expediency of using neural network analysis tools based on biometric parameters, which can be registered using common computer tools, is shown. It was determined that in the distance learning system, the specified biometric parameters should primarily include a person's face and voice. It is justified that the following should be included in the list of basic parameters for evaluating the effectiveness of means of recognizing the emotional state of a member of a distance learning system based on neural network analysis of a person's face and voice: the completeness of recognition of basic emotions; ability to recognize complex emotions; the ability to recognize an emotional state; recognition accuracy; computational complexity of recognition; the ability to recognize emotions without prior recognition of a person. As a result of the research of well-known technologies for recognizing emotions and persons by face and voice, a list of additional parameters was determined, which provide the possibility of evaluating the effectiveness of the specified technologies when they are used in the distance learning system. Taking into account the proposed performance evaluation parameters, it is shown that from the point of view of using modern emotion recognition tools in the distance learning system, their critical shortcomings are related to: low accuracy of recognition of the nomenclature of both basic and complex emotions; high computational resource intensity; inability to recognize emotions based on a complex analysis of several biometric parameters; low integration with means of identity recognition; the difficulty of recognizing an emotional state. It is substantiated that the prospects of further research in the field of the application of emotional state recognition tools in the distance learning system should be correlated with their adaptation to the expected conditions of use and their integration with the word recognition system in the member's voice signal.