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Vidya Samiksha Kendra — Gujarat's AI-based dropout early-warning system

India · Gandhinagar · See the India profile

Gujarat's Vidya Samiksha Kendra uses AI analytics on attendance and assessment data to flag dropout risk for 11.5 million students in 54,000+ schools. State figures report 167,446 at-risk pupils retained in 2025-26; replicated in 14 Indian states since 2023.

11.5 million students
Students covered
54,000+ schools
Schools covered
5 billion
Data points analysed annually (annual)
167446 students
At-risk students prevented from dropping out (2025-26)
90212 children
Previously dropped-out children re-enrolled (2025-26)
118234 students
Newly flagged at-risk students (2025-26)
15 %
Reduction in absenteeism (Sabarkantha district) (one academic year)
14 states (+1 union territory)
States/UTs that replicated the model (since 2023)
Vidya Samiksha Kendra — Gujarat's AI-based dropout early-warning system

Details

Maturity
Established
Promoter
Gujarat State Education Department (Government of Gujarat)
Period
2021–present
Keywords
primary & secondary education, government, early-warning system, data analytics, dropout prevention

Context

Vidya Samiksha Kendra is a state-run education command centre established by Gujarat's Department of Education in Gandhinagar, inaugurated in June 2021 and visited by Prime Minister Narendra Modi in April 2022. It applies artificial intelligence, machine learning and big-data analytics to more than 500 crore (5 billion) data points collected annually — attendance, assessment results, teacher performance and student socio-economic and demographic data — covering roughly 1.15 crore (11.5 million) students across 54,000+ government schools.

Objectives

VSK's AI-based Early Warning System aims to predict dropout likelihood among students in Classes 1-8 so that at-risk pupils can be identified early and retained in school, while a linked Child Tracking System seeks to re-enrol children who have already dropped out.

Activities

The system continuously analyses attendance, assessment, and demographic data to flag at-risk students, triggering targeted interventions by teachers and counsellors; the Child Tracking System separately follows up with already-dropped-out children to bring them back into school.

Results

According to Gujarat's June 2026 Shala Praveshotsav announcement, VSK helped prevent 167,446 at-risk students from dropping out in the prior year, re-enrolled 90,212 previously dropped-out children, and newly flagged 118,234 more students as at-risk. A NITI Aayog case study separately documents a 15% reduction in absenteeism in Sabarkantha district within one academic year. The World Bank, OECD and UNICEF have cited the model as a best practice, and it has been replicated by 14 other Indian states and one union territory since 2023.

Conclusions

Evidence should be read with caveats: the headline dropout-prevention figures come from a state-government announcement echoed by wire services rather than an independent audit or peer-reviewed study, and IIT Bombay's Centre for Education Technology has publicly noted that VSK's predictive-analytics layer could be further enhanced with predictive algorithms, indicating the AI component is real but not yet at the frontier of sophistication.

Implementation

Indicative cost
High (€500k–€5M)
Time to results
Long (> 3 years)

Data sources

Where this practice's information was retrieved from, and when.

Attachments

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