Data-Driven Quality Management in Education (based on Data of Moscow schools)

Stable growth of the educational data market poses new challenges for managers, which require improving the existing quality management system, including data analysis practices. Each year, large territorial education complexes are included in the rating of contributions to the quality of education of Moscow students. On the one hand, they have an advantage in a large contingent due to the increasing coefficient of effectiveness. On the other hand, building an effective quality management system becomes more difficult because of the scale. The study is devoted to describing the existing practices for managing the quality of education in Moscow schools with a large contingent, which allow tracing the dynamics of learning outcomes not only for the entire school but also for the educational trajectory of each student. As part of the study, interviews were conducted with the directors of schools with over 3,000 students and who received grants for their contribution to the quality of education of Moscow students between 2021 and 2023. The unified context of the Moscow education system allows management teams of educational organizations in Moscow to use the results of the study. Keywords: data-driven decision making, quality of education, Moscow education