Instrumental support of technologies for organizing group training for the development of soft skills in data science and analytics

Abstract

The article deals with the problem of organizing training for data scientists and data analytics specialists using information technologies. The authors analyzed the current sets of competencies of data science and analytics, identified the problems of organizing their development, considered modern trends in the instrumental support of the learning process. Particular attention is paid to the peculiarities of the development of soft skills in data science and analytics, which should be taken into account in systems and platforms for learning support when building models for the formation of personalized content and learning paths within the course. The necessity of creating a multi-agent software application to support the pedagogical design of the course is substantiated, which allows to adapt the capabilities of modern software systems and learning platforms to increase the efficiency of group interaction and the formation of soft skills necessary in the implementation of data analysis projects. The results of the conceptual design of a multi-agent application integrated with modern learning platforms are presented: a UML diagram of use cases is proposed that provides support for the personalization of training not only at the individual, but also at the command level, the base classes of agents are highlighted and an ontological model is developed to support the formation of soft skills in data science and analytics, directions of further research are determined. The results obtained will be useful to support the formation of a full set of competencies for data science and analytics, as well as to increase the efficiency of group work and support the personalization of content in a hybrid or online learning format, both in the higher education system and in corporate divisions.