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UID: ED-20251204-IN-06

Source

UDISE+, Ministry of Education

Last Updated

December 16, 2025

Time Range

As of FY’2025

Periodicity

Annual

Unit

Absolute Number

Sector

Education

Next Update

2026

Indicator Summary

Overview

The indicator “Number of Shift Schools” reflects how education systems manage limited infrastructure in response to growing student populations and space constraints. Shift schools operate in two or more time blocks, such as morning and afternoon shifts, allowing the same physical facilities to serve a larger number of students. This makes the indicator a valuable proxy for understanding capacity pressure within the school education system. A high number of shift schools often signals shortages in classrooms, land, or funding for new school construction, particularly in densely populated urban areas or rapidly growing regions. While shift schooling can improve access to education by accommodating more students, it may also reduce instructional time, limit extracurricular activities, and strain teachers and facilities. These factors can have implications for learning outcomes, student well-being, and teacher effectiveness.

From a policy and planning perspective, tracking the number of shift schools helps governments and stakeholders assess infrastructure adequacy, plan school expansion, and prioritise investments in new buildings or classroom additions. It also supports equity analysis by identifying areas where students may receive fewer learning hours due to systemic constraints. For researchers and decision-makers, this indicator provides critical insight into the trade-offs between access and quality in education delivery, supporting evidence-based planning for sustainable, long-term education infrastructure solutions.

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Citation information

UDISE+, Ministry of Education. (2025). Number of Shift Schools in India by School Management and School Category, As of FY’2025 (360 Analytika, Ed.) [Dataset]. https://360analytika.com/number-of-shift-schools-in-india/

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