Education Department implements AI-based Early Warning System (EWS) to identify students at risk of dropping out from schools
Nearly 1.68 Lakh At-Risk Students Identified Through AI-Based EWS; Special Attention to Ensure Continuation of Education
Identified Students and Parents to Be Invited During Shala Praveshotsav 2025; Importance of School Education to Be Emphasized for Child’s Progress
Gandhinagar, 23 June 2025: As the then Chief Minister of Gujarat, Shri Narendra Modi, launched the Shala Praveshotsav and Kanya Kelavani Rath Yatra programmes in 2002-03, ensuring that every eligible child receives their rightful access to primary education. As a result of these programmes, Gujarat has witnessed a significant reduction in the school dropout ratio among students receiving primary education. In the year 2001-02, the dropout ratio of students from Classes 1 to 8 was 37.22%, which declined to 2.42% in the year 2023-24.
However, the Government of Gujarat aims to reduce the school dropout ratio to nearly zero at the primary, secondary, and higher education levels. To achieve this goal, under the leadership of Chief Minister Shri Bhupendra Patel, the state’s education department has implemented an Artificial Intelligence (AI)-based Early Warning System (EWS) to prevent school dropouts among students. This system identifies potential dropout students in advance, preventing them from leaving school and ensuring they complete their education.
Currently, around 1 crore students are studying in government primary schools (Grades 1 to 8) in Gujarat. Among these, the Early Warning System (EWS) has so far identified nearly 1,68,000 students — less than 2% — who are at potential risk of dropping out. The state government will ensure that these 1,68,000 students identified by EWS continue their schooling. To support this, these students and their parents will be invited to the Shala Praveshotsav, where they will be sensitized about the importance of completing school education for the child’s development and progress. In this way, the state government is actively working toward achieving the goal of bringing the school dropout rate close to zero.
What is the AI-based Early Warning System (EWS)?
The AI-based Early Warning System (EWS), built on a fully scientific approach, uses data such as age, gender, disability status, school performance, attendance, and assessment records of every student studying in primary schools (Classes 1 to 8) to predict potential dropout cases in advance and issues alerts to take preventive actions.
The system uses algorithms to identify patterns in the data to detect students at risk of dropping out. This enables timely intervention before a student leaves school. Major contributing factors for student dropouts include frequent absenteeism, poor academic performance, health issues or physical disabilities, and behavioral problems. In addition, school-related information such as school type (government, aided, private, etc.), multigrade classrooms, school infrastructure, and family-related data such as economic status, migration, family beliefs about education, number of children in the family, and demographic factors are also used to identify potential dropout students.
Thus, the purpose of this system is to identify students at risk of dropping out based on key indicators. Once identified, these students will be supported through preventive response strategies and interventions tailored to their specific needs to ensure they remain enrolled in school.
Identification of around 1,68,000 students at risk of dropout through EWS
It is noteworthy that, so far, the EWS has identified approximately 1,68,000 students at risk of dropping out. The list of such students studying in all government and grant-in-aid schools across the state has been made available to schools through the login of the Child Tracking System (CTS). Based on this list, action will be taken during the Shala Praveshotsav and Kanya Kelavani Mahotsav-2025 through the Block Resource Centre (BRC) Coordinator, Cluster Resource Centre (CRC) Coordinator, school principals/head teachers, and the School Management Committee (SMC). In addition, appropriate directives, reviews, and monitoring will be conducted at the district level to take proactive steps to prevent potential student dropouts.
Students identified as at-risk by the EWS and their parents will be invited to the upcoming Shala Praveshotsav programme. Parents will be made aware of the importance of completing school education for their child’s development and progress. Furthermore, careful measures will be taken to ensure that parents are treated with respect and dignity, and do not face any negative or embarrassing experiences.
After identifying the factors related to the potential dropout of students, discussions will be held with their parents to prevent the child from leaving school. School Management Committee meetings will address how to ensure the child completes their education and remains enrolled. When the new academic year begins, the School Management Committee will ensure that students identified as at-risk definitely get enrolled and attend school regularly.
Thus, through the Early Warning System, potential dropout students will be identified and prevented from leaving school through public awareness, parental engagement, and community cooperation.
