AI-led Competency-Based Assessments – Rajasthan Council of School Education
AI-led Competency-Based Assessments
Problem
- Assessment practices varied widely because schools and teachers designed and evaluated tests independently.
- Teachers lost significant instructional time in manual answer-sheet correction and data entry on state portals.
- Multiple-choice assessments measured final answers but did not capture reasoning, creativity, or conceptual understanding.
- Regular assessments were conducted, but lacked a structured, large-scale remediation framework.
- Traditional report cards were difficult for parents, especially rural and disadvantaged families, to interpret and act upon.
Solution
- A standardised competency framework was developed for Grades 3–8 in Mathematics, Hindi, and English.
- Centrally printed, paper-based assessment papers were distributed to ensure inclusion across low-connectivity schools.
- Teachers used the Shikshak App to scan answer sheets through mobile phones.
- AI-OCR and AI-based rubric systems enabled automated evaluation of objective and handwritten subjective answers.
- Competency-wise reports, remediation recommendations, learning resources, and Mega PTMs linked assessment data with classroom and parental action.
Outcomes
- Rajasthan implemented a statewide competency-based assessment system covering more than 45 lakh students.
- AI-enabled bilingual handwritten subjective answer evaluation in government schools at large scale.
- Student misconceptions, reasoning abilities, and competency gaps were identified for targeted remediation.
- Automated scanning and evaluation reduced teachers’ manual correction and data-entry burden.
- More than 20 lakh parents participated in Mega PTMs and received competency-based report cards.
SKOCH Award Nominee
Category: State Government – Elementary Education Department
Sub-Category: secState Government – Elementary Education Department
Project: AI-led Competency-Based Assessments
Start Date: 3-01-2022
Organisation: Rajasthan Council of School Education
Respondent: Rashmi Sharma
https://education.rajasthan.gov.in/rcse/#/home/dptHome
Level: Club Star
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Case Study
The AI-led Competency-Based Assessment initiative of the School Education Department, Government of Rajasthan, represents a large-scale transformation in public school assessment and learning improvement. Launched in 2022 by the Rajasthan Council of School Education, the initiative was designed to address post-pandemic learning gaps and build a competency-based, data-driven education system aligned with the vision of NEP 2020. Covering more than 45 lakh students across government schools, the programme sought to move beyond traditional marks-based testing and create a reliable system for understanding what students actually know, where they struggle, and how teachers and administrators can respond effectively.
Before the intervention, assessment practices across schools varied widely. Teachers often designed and evaluated their own tests, which made results difficult to compare across classrooms, schools, districts, and the state. Manual correction of answer sheets and data entry into state portals consumed significant teacher time, reducing the hours available for classroom instruction and student support. Existing multiple-choice assessments measured only final answers and did not capture reasoning, creativity, misconceptions, or conceptual understanding. Although assessments were conducted regularly, the system lacked a structured remediation framework. Parents, especially in rural and disadvantaged communities, also found conventional report cards difficult to interpret, limiting their ability to support children’s learning at home.
To address these challenges, Rajasthan developed a standardized competency framework for Grades 3 to 8 in Mathematics, Hindi, and English. Based on this framework, child-friendly and competency-based assessment papers were prepared and centrally distributed to government schools. The programme followed a hybrid paper-plus-digital model, ensuring that students could continue writing assessments on paper even in schools with limited digital infrastructure. After the tests, teachers used the Shikshak App on their mobile phones to scan answer sheets. AI-OCR technology enabled automated evaluation of objective responses, while AI-based rubric systems were later piloted to assess handwritten subjective answers in Hindi and English.
The implementation evolved over time into a full data-driven remediation system. Assessment data was processed centrally to generate competency-wise reports at student, classroom, school, district, and state levels. These reports gave teachers and administrators near real-time visibility into learning gaps and helped guide classroom interventions, teacher support, academic planning, monitoring, and resource allocation. The system also introduced simplified competency-based report cards using formats such as star ratings, making learning progress easier for parents to understand. Mega Parent-Teacher Meetings were organized to share these reports and encourage families to participate more actively in children’s education.
The outcomes were significant. Rajasthan successfully implemented a statewide competency-based assessment system at census scale, covering more than 45 lakh students. The initiative reduced the burden of manual correction and data entry, allowing teachers to focus more on teaching and remediation. It enabled deeper analysis of student misconceptions, reasoning abilities, and competency gaps, strengthening targeted academic interventions. More than 20 lakh parents participated in Mega PTMs, improving community engagement with learning outcomes. The programme also achieved a major technological breakthrough by using AI to evaluate bilingual handwritten subjective responses in government schools.
For more information, please contact:
Rashmi Sharma at spdrmsaraj@gmail.com
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