Moscow City University, National Research University Higher School of Economics
Personal homepage Professional homepagehttps://www.hse.ru/en/org/persons/58562690
ORCID more infohttps://orcid.org/0000-0002-1216-5043
GitHub more info
Moscow City University, Professor: Institute of Digital Education - http://digida.mgpu.ru
National Research University Higher School of Economics, Professor: Institute of Education / Department of Educational Programmes. Leading Expert: Institute of Education / Laboratory for Digital Transformation of Education - 2019 – present
2016 – present Leading Researcher at Moscow City University, Educational policies & educational practices
2018 – 2020 World Bank, Consultant. Children Learning to Code: Essential for 21st Century Human Capital
2011 - 2019 - Co-founder, chief community officer at WikiVote!
Educational network - Letopisi.org 2006 – present, Co-founder, chief community officer
Scientific project “Mobile and ubi-learning”, 2009 - 2011
ABM, wiki, NetLogo, StarLogo Nova, R, Collaboration
This agent-based model simulates the lifecycle, movement, and satisfaction of teachers within an urban educational system composed of multiple universities and schools. Each teacher agent transitions through several possible roles: newcomer, university student, unemployed graduate, and employed teacher. Teachers’ pathways are shaped by spatial configuration, institutional capacities, individual characteristics, and dynamic interactions with schools and universities. Universities are assigned spatial locations with a controllable level of centralization and are characterized by academic ratings, capacity, and alumni records. Schools are distributed throughout the city, each with a limited number of vacancies, hiring requirements, and offered salaries. Teachers apply to universities based on the alignment of their personal academic profiles with institutional ratings, pursue studies, and upon graduation become candidates for employment at schools.
The employment process is driven by a decentralized matching of teacher expectations and school offers, taking into account factors such as salary, proximity, and peer similarity. Teachers’ satisfaction evolves over time, reflecting both institutional characteristics and the composition of their colleagues; low satisfaction may prompt teachers to transfer between schools within their mobility radius. Mortality and teacher attrition further shape workforce dynamics, leading to continuous recruitment of newcomers to maintain a stable population. The model tracks university reputation through the academic performance and number of alumni, and visualizes key metrics including teacher status distribution, school staffing, university alumni counts, and overall satisfaction. This structure enables the exploration of policy interventions, hiring and training strategies, and the impact of spatial and institutional design on the allocation, retention, and happiness of urban educational staff.
Under development.