Student project communities big data analysis in working with knowledge systems: Cognitive visualization

The results of a study are characterized -- cognitive visualizations of big data based on the materials of digital footprints of student project communities’ activities on the creation of knowledge in education . The presentation of these results in combination with the subject of the study – the specified footprints – is the basis for the relevance of the paradigm of visual semiotics to the tasks of this project. The development of the interdisciplinary Science of Team Science field of knowledge is based on the developments and research of project teams as creators of new knowledge. Such studies use methods of network analysis of big data of project team members as cognitive activity footprints. Agents of new knowledge (conductors of new ideas) and knowledge attractors – meaning-forming units of information developed by followers of the agent of new knowledge – are identified. Experiments on studying the agency of new knowledge were conducted on the platforms of Wiki libraries, in studies of scientific citation of new knowledge on the publication platforms eLIBRARY, Scopus, Web of Science, but the question of studying student project teams jointly developing new technological products on the platform of university technological entrepreneurship – Univertechpred – has not been raised. The need for such a study is due to the fact that didactic forms of work with students’ project-based knowledge are institutionalized through federal projects of the Ministry of Science and Higher Education: “startup as a diploma”, “platform of university technological entrepreneurship”. However, the nature of student project teams’ activities on creating new knowledge and technological products has not been explored. The study used SNA (Social Network Analysis) methods, through which the density, intensity, and spatial coordination of social connections in the network (on the digital platform the student project team works) are analyzed. The aim of the study is to examine the cognitive mechanisms of student project communities’ activity in working with knowledge systems. In the study, as the main source of big data for analyzing the activities of student project teams to create new knowledge and new technologies, footprints of digital searches by students for patent analogues (on the platforms of Rospatent, the Moscow Innovation Cluster) were used to develop projects presented on the platform of university technological entrepreneurship. Also, based on big data methods, digital footprints of the authors-creators of the electronic program code for the functioning of the developed student projects were studied. The study was conducted on the GitHub platform, which has the ability to store the project repository and all its changes. The big data method was also used to study digital footprints of authors of educational courses in the network repositories of the open digital educational platform SkillSpace – the network cognitive activity of youth teams to create educational online courses on the open platform was studied. All of the above digital platforms have interactive services for organizing activities to create new knowledge, a technological product of a student project team. The study revealed that the clustering indicator of big data in the form of digital footprints of student project communities characterizes the degree of interaction between the interdisciplinary neighbors of the considered agent of new knowledge. For the development of digital educational environments (DEE) of universities, the results of the study indicate the need to integrate digital services for organizing student teamwork for specific educational, research and project tasks into universities’ DEE. The study of the practices of student project communities with various knowledge systems ((a) research knowledge in the form of articles on Wiki platforms; (b) knowledge about intellectual products in the form of patent archives on WIPO platforms; (c) knowledge of AI (artificial intelligence) codes in the form of Program-Code in source code editor applications) revealed the specifics of the practices of student project communities with knowledge of various types. Based on the results of the study, it can be concluded that big data technologies have a significant potential in the study of project teams creating new knowledge on digital platforms. The results of the study are theoretically significant for the development of scientific fields – information anthropology, pedagogical semiotics, cybernetics of digital educational environments, cognitive science. The practical significance of the study is related to the applicability of the identified characteristics of the activities of student project teams (startup developers) in educational practice.

big data, cognitive networks, knowledge management, network analysis, project communities, digital platforms, digital footprints