Keyword: «electronic interactive communication»

Modernization of higher education opens up prospects for using artificial intelligence technology to improve the quality of training for library specialists. The use of generative neural network services meets both the requirements for training programs for highly qualified librarians and the requirements for the level of their demanded soft skills development. The authors examine the problem of justifying the effectiveness of including artificial intelligence technology in the training process of library specialists. The purpose of the study is to explore the potential of using generative neural networks in training librarians to improve the quality of their education. The scientific novelty lies in the fact that the didactic potential of using generative neural networks in training specialists for library and information activities is justified. Theoretical significance – the identified didactic capabilities are supported by electronic interactive communication in the educational environment to develop soft skills, the most popular in digital society. The generative neural network is considered as a class of artificial neural networks that are able to create new information based on training data. The choice of service is justified by the type of information processed and the implemented labor functions of the librarian. 68 bachelors of the Orel State Institute of Culture were involved. The area of training 51.03.06 Library and information activities, specialization – "Digitalization of information resources and processes". Assessment of the quality (level) of training was carried out using the materials of the fund of complex qualification tasks. The 2-Pearson criterion was used for statistical processing of data. The system of work on the use of neural network services in training librarians on materials of a specific discipline is described: the study of basic concepts, information services, etc. The peculiarity of the proposed electronic interactive interaction is the adaptation of the content of requests solved by the neural network according to the specifics of the area of training. The authors conclude that services contribute to improving the quality of training due to the following didactic capabilities: presentation of information in various forms, automation of calculations, big-data analysis, decision making support, etc. Difficulties are also highlighted: constant updating of the functionality of services, English-language interface, compliance with copyright norms and ethics of interaction on the network. The results obtained can be used to update training programs for librarians, advanced training courses, and the content of webinars in the field of library and information services.