The Third Annual International Symposium “Education and City: Education and Quality of Living in the City” (Education and City 2020)
Network analysis methods are actively used to research the behavior of digital repository users who utilize and create digital objects. At the same time, the research into the collective behavior of a group of participants who are members of the same school is much less common. The library of the Moscow Electronic School is a rather complicated system with multiple roles offered to users. The actors of the repository are teachers, students, parents, and publishers – anyone performing any actions with the objects. In this study, the school is seen as an actor performing actions with objects – lesson scenarios within the Moscow Electronic School repository of digital objects. Within the study, the authors compare the sociograms of schools that unite teachers and the scenarios created by the teachers and divide schools into factions based on network indicators in sociograms. The main method of presenting and analyzing data is network analysis and sociogram creation. The authors identify two types of networks: the network of single participant’s relationships and the network of relationships of teachers from a single school. The authors not only describe the data structure in the Moscow Electronic School system that records the digital trace of every individual and collective user but also create a digital map that reflects the dynamics of actions in the Moscow Electronic School system and identify the indicators that characterize the common activity of key participants. Moreover, the authors identify graph factions for schools that characterize the degree of interaction between teachers: disconnected groups, sparse graphs, crystallization centers, dense graphs.
This article presents generalized model of collaborative actions, during which participants create, modify, and estimate digital objects. Such activities can be observed in numerous network communities. A prominent example is the repository of lesson scenarios of Moscow Electronic School (MES). The combination of methods of agent-based modeling and network analysis is used in the work. Using NetLogo environment in the frames of the model, an artificial community has been developed, where teachers-agents interact with scenarios-agents. Teacher-agent determines whether there are potential scenarios in his environment to be contacted with. If such scenarios are available, then the agent selects the nearest one and makes a step towards it. If the scenario has been opened by one of the teachers, then this is already an author’s scenario and the teacher-agent takes an action to reuse it. Variants of the reuse can be preset so that to correspond to the actions allowable in the environment of MES repository for learning scenarios: review, addition to bookmarks, running the scenario, downloading, using in home assignments. All these actions of teachers regarding scenarios are logged, then the log records are transformed into bipartite graph. The experiments demonstrate that while the area of participant scenarios is expanded, not only the general number of links among participants increases but also large networks of participants are subdivided into smaller and densely interconnected groups. One of the control trends of participant activities is in the use of multiagent-based modeling as a tool of collective reflection of teachers cooperating on the basis of MES.