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Digital Economy: 2021: Pocket Data Book
M.: HSE, 2021.
It Can’t Be Taught Online: Applied Sciences during the Pandemic
Transition to distance learning during the COVID‑19 lockdown in spring 2020 was a challenge to the education system in general and higher education in particular. Applied Sciences were unanimously recognized as the most affected due to their focuson practical skills, being closely tied to the institutional infrastructure, and a moderate curriculum digitalization. This article describes student experiences during the spring semester of academic year 2019/20, using data obtained from 30 interviews with students in Engineering, Technology & Applied Sciences, Health & Medical Sciences, and Arts & Culture degrees. Delivery of lectures and practical classes, placements, dissertations, and faculty–student interactions are analyzed. Findings are consistent with the widely discussed perception of education during the pandemic not as distance learning but rather as emergency remote teaching that requires supportive measures to compensate for time loss in learning as well as solutions to technical and methodological issues.
Educational studies. 2021. No. 1. P. 115-137.
Agent-based modeling of teacher interaction within a repository of digital objects
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.
In bk.: The Third Annual International Symposium “Education and City: Education and Quality of Living in the City” (Education and City 2020). Vol. 98. SHS Web of Conferences, 2021. Ch. 05013. P. 1-7.
How Do The Characteristics Of The Environment Influence University Efficiency? Evidence From A Conditional Efficiency ApproachThis paper explores the black box behind efficiency measurements in higher education and define the determinants of university efficiency. Particularly, it investigates how the efficiency of universities is affected by the characteristics of the territory in which they operate. We propose an analysis that combines two perspectives: 1) the resource dependence theory, suggesting that the location of university can determine the amount of resources available to it; 2) institutional isomorphism, according to which the characteristics of other higher education institutions located in the same area may shape the university production function and the efficiency of its operations. In order to test this framework we use the data on Russian universities and non-parametric conditional order-m efficiency estimator with two categories of exogenous variables. The first group includes the social, economic and cultural characteristics of the region where the university is located. The second set includes the characteristics of other higher education institutions located in the same region. Our findings highlight that the managerial efficiency of universities is strongly associated with the characteristics of the environment in which they operate
Economics/EC. WP BRP. Высшая школа экономики, 2020. No. 238.
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