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Gujarat Implements AI-Based 'Early Warning System' To Identify & Prevent School Dropouts | How Does It Work?

The government plans to ensure that the 1,68,000 students identified for potential dropout, remains enrolled in school through several methods including, 'Shala Praveshotsav', an event organised to spread awareness about the importance of completing school education.

Indian schoolboy in classroom | Representative image/Getty Images

Gujarat government has implemented an artificial intelligence based 'Early Warning System' in its schools to prevent dropouts over the recent years. As per recent data, EWS has identified nearly 1,68,000 students which is less than 2 per cent of the total number of enrolled students from Grades 1 to 8, who are at potential risk of dropping out.

The Early Warning System launched in aimed to identify potential dropout students and prevent them from leaving school through public awareness, parental engagement and community cooperation.

According to the government's recent press release, the dropout ratio of 37.22 per cent for students in Classes 1 to 8 in the academic year 2001-02 has come down to just 2.42 per cent for the year 2023. The government thanked various educational initiatives launched by the government, including the Shala Praveshotsav and Kanya Kelavani Rath Yatra programmes, initiated by then-Chief Minister Narendra Modi in 2002-03 that aimed to ensure access to primary education to every eligible child.

Gujarat Government Uses AI-Based System To Track School Dropouts

The Government of Gujarat now aims to reduce the school dropout ratio to nearly zero at the primary, secondary, and higher education levels.

Thus, the state's education department has implemented an AI-based Early Warning System to prevent school dropouts.

This system launched is aimed to identify potential dropout students and prevent them from leaving school so that they complete their education.

According to the current data released by the government, there are around 1 crore students studying in government primary schools which is from Grades 1 to 8 in Gujarat.

Reportedly, EWS has identified nearly 1,68,000 students which is less than 2 per cent of the total, who are at potential risk of dropping out.

The government now plans to ensure that these 1,68,000 students continue their schooling and to make that happen, a 'Shala Praveshotsav' will be organised where these students and their parents will be invited to be aware about the importance of completing school education.

How Does AI-Based Early Warning System Work?

EWS works based on the provided data regarding the age, gender, disability status, school performance, attendance and assessment records of every student who are enrolled in the state schools.

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Reportedly the data of the students studying in all government and grant-in-aid schools across the state were available through the login of the Child Tracking System.

Algorithms have been created for the system to identify patterns in the data to detect students who are at risk of dropping out.

The algorithm detects the potential students based on their frequent absenteeism, poor academic performance, health issues or physical disabilities, and behavioural problems.

The Al-based Early Warning System (EWS), built on a fully scientific approach, uses data such as studying in primary schools (Classes 1 to 8) to predict potential dropout cases in advance and issues alerts to take preventive actions.

The system also identifies the type of school these children go to, the infrastructure of those schools, classrooms and also the family structure that they belong to which includes factors like economic status, migration, family beliefs about education, number of children in the family and other demographic factors.

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The system will issue alerts for the authorities before the student actually drops out so that there is a timely intervention.

These methods of intervention include events like Shala Praveshotsav and Kanya Kelavani Mahotsav-2025 which will be conducted in the presence of the Block Resource Centre Coordinator, Cluster Resource Centre Coordinator, school principals/head teachers, and the School Management Committee.

As per the release, the School Management Committee will hold meetings to address how to ensure the child completes their education and remains enrolled. When the new academic year begins, the committee will ensure that students identified as at-risk definitely get enrolled and attend school regularly.

The government also aims to conduct appropriate directives, reviews, and monitoring prevent potential student dropouts.

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