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UID: ED-20251129-IN-01

Source

UDISE+, Ministry of Education

Last Updated

December 4, 2025

Time Range

As of FY’2025

Periodicity

Annual

Unit

Absolute Number

Sector

Education

Next Update

2026

Indicator Summary

Overview

The number of schools by school management and school category is an important indicator of a nation’s educational system’s capacity, equity, and structure. The distribution of schools across different learning stages is demonstrated by school management categories, such as Foundational and Preparatory, Middle, and various Secondary levels. School categories like State Government, Government Aided, Private Unaided, Central Government, and Others reflect who controls and funds these schools.

This measure hold substantial importance because it illustrates the availability, quality, and accessibility of education across geographical areas. From early childhood to upper secondary education, a balanced distribution guarantees that students have suitable learning pathways. It also helps identify gaps—such as shortages of secondary schools or uneven concentration of private institutions—that may limit educational opportunities.

For policymakers, these data guide decisions on infrastructure investment, teacher deployment, curriculum planning, and policy interventions aimed at improving equity. School distribution gives researchers and analysts information about regional differences, public versus private participation, and socioeconomic trends. Additionally, it aids in the forecasting of resource requirements and the planning of focused programs like scholarships, digital learning, and capacity-building projects. Overall, this metric is critical for not only ensuring education access, quality, but also long-term human capital development.

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Citation information

UDISE+, Ministry of Education. (2025). Number of Schools by School Management and School Category (360 Analytika, Ed.) [Dataset]. https://360analytika.com/number-of-schools-by-school-management-and-school-category/

Note: Please ensure proper attribution when using this data in your research or publications.