Using Data to Improve Teaching and Learning in India

Leveraging Administrative Data for Educational Outcomes

Introduction

Quality of education at the school level is a major area of concern in India. Despite significant enrollment rates and infrastructure development progress over the past decades, learning outcomes remain persistently low. The National Achievement Surveys (NAS) conducted by the NCERT have consistently highlighted substantial gaps between expected and actual learning levels across states. A significant percentage of students in grade 5 struggle with grade 2-level reading and arithmetic skills, demonstrating a profound learning crisis that requires urgent attention.

This situation calls for evidence-based interventions and policy reforms. Data-driven decision-making offers a promising approach to diagnosing problems, designing targeted interventions, and monitoring progress. In particular, administrative data—already collected by education departments and schools—represents an underutilized resource that could transform educational planning and delivery.

The Current State of Administrative Data in Education

Types of Administrative Data Available

India has established several systems for collecting administrative data in education:

1. Unified District Information System for Education+): Collects comprehensive data on school infrastructure, enrollment, teachers, and facilities.
2. National Achievement Survey (NAS): Provides assessment data on learning outcomes across grades and subjects.
3. State-level Management Information Systems (MIS): Despite UDISEPlus, many states have developed systems to track attendance, mid-day meals, teacher deployment, and other operational aspects.
4. School Data Management System (SDMS): A new initiative started in 2022-23. It is a collection under UDISEPlus that tracks individual student records and progress, enabling personalized monitoring of achievement levels.
5. School-level Records: Apart from others, schools used to maintain attendance registers, continuous and comprehensive evaluation (CCE) records, and internal assessment data.

Limitations in Existing Data Systems

UDISE+ Limitations

1. Focus on Infrastructure Metrics: UDISE+ heavily emphasizes physical infrastructure and enrollment data, with limited attention to teaching-learning processes and outcomes.
2. Annual Collection Cycle: The yearly data collection cycle means information quickly becomes outdated for operational decision-making.
3. Data Verification Challenges: Limited mechanisms exist to verify the accuracy of self-reported school data, leading to questionable reliability.
4. Underutilization in Planning: Despite its comprehensive nature, UDISE+ data is rarely integrated effectively into annual planning processes under Samagra Shiksha.
5. Limited School-Level Use: Schools often view UDISE+ data collection as a compliance exercise rather than a tool for improvement.
6. SDMS data has yet to be made public, and it is unknown how it is being utilized at different levels, starting from schools.

NAS Limitations

1. Lack of Follow-Up Mechanisms: No systematic follow-up occurs after NAS is conducted. Results are published but rarely translated into specific interventions, but follow-up workshops were conducted after NAS 2021.
2. Aggregated Reporting: NAS typically reports aggregated data at district or state levels, limiting its usefulness for school-level improvement.
3. Timing Delays: Though reduced during the recent survey, substantial time lags between assessment, analysis, and reporting still lessen the relevance of timely interventions.
4. Limited Integration with Planning: NAS results are minimally integrated into annual planning under Samagra Shiksha, creating a disconnect between identified learning gaps and resource allocation.
5. Absence of Longitudinal Analysis: The cross-sectional nature of NAS makes it challenging to track progress over time for cohorts of students.

Structural Challenges in Data Management

1. Separation of Data Collection and Utilization: Those engaged in data collection (typically MIS officers) are generally not involved in teaching and planning. MIS officers are primarily technical personnel who spend the entire year engaged in data collection processes across different portals, with limited understanding of educational contexts.
2. Multiple Disconnected Portals: Schools must report similar information to various government portals, creating duplication and increasing the administrative burden.
3. Limited Use in Annual Planning: Administrative data is restricted under Samagra Shiksha, resulting in plans that may not address the most critical needs.
4. School Record Maintenance Issues: Many schools maintain records inconsistently or incorrectly, undermining the foundation of all administrative data systems. Schools must use the same sets of records prescribed by the high-level committee constituted by the Ministry during 2011-12.
5. Capacity Constraints: Teachers and administrators often lack the training and skills to interpret and use data effectively for instructional improvement. Lately, not all states have conducted capacity-building programs for the respondents.

Global Examples of Effective Data Use in Education

Brazil’s IDEB System

Brazil’s Basic Education Development Index (IDEB) combines student performance data with progression rates to create a composite school quality indicator. This system enables targeted support to underperforming schools and has contributed to Brazil’s significant improvements in learning outcomes. The transparency of school-level IDEB scores also creates accountability and community engagement.

Chile’s SEP Program

Chile’s Preferential School Subsidy Program (SEP) uses assessment data to identify underperforming schools and provides additional resources based on improvement plans. Schools receive technical assistance and must demonstrate progress against specific targets. This data-driven approach has shown positive impacts on learning outcomes for disadvantaged students.

Vietnam’s Balance Scorecard

Vietnam implemented a balanced scorecard approach that tracks multiple school performance indicators beyond test scores; this includes leadership practices, teacher collaboration, and community engagement. The system provides schools with regular feedback and comparison data, enabling continuous improvement cycles.

Kenya’s Tusome Program

Kenya’s Tusome (“Let’s Read”) program uses tablet-based data collection to monitor real-time classroom instruction and student progress. Coaches visit classrooms, record observations, and provide immediate feedback to teachers. The aggregated data helps identify systemic issues and successful practices across schools.

Improving Learning Levels Through Data

The Potential of SDMS for Personalized Learning

The School Data Management System (SDMS) significantly advances India’s educational data infrastructure. By maintaining including the updatation of individual student records and tracking progress over time, SDMS offers several advantages:

1. Personalized Tracking: Teachers can monitor each student’s achievement levels and progress, enabling tailored interventions.
2. Early Identification: Learning difficulties can be detected earlier, allowing for timely remedial support.
3. Progression Analysis: Student progress can be tracked across grades, highlighting systemic strengths and weaknesses.
4. Evidence-Based Grouping: Students can be grouped based on actual learning levels rather than age or grade for more effective teaching.
5. Comprehensive Teacher Training: Develop specialized data literacy and utilization modules for pre-service and in-service teacher education programs, including practical SDMS and NAS data applications.
6. School Leadership Development: Train principals and school management committees to interpret and act on data from multiple sources, including proper maintenance and utilization of school records.
7. District-Level Data Teams: Revamp dedicated teams at the district level that include both technical specialists and educational experts to bridge the gap between data collection and educational planning.
8. MIS Officer Role Expansion: Transform the role of MIS officers from mere data collectors to data analysts and facilitators who can support educators in understanding and using data.

However, realizing these benefits requires addressing implementation challenges and building capacity among educators to utilize this data effectively. Better to establish formal mechanisms to incorporate SDMS data into Samagra Shiksha annual planning processes.

Case Studies of Effective Data Use in  States

Tamil Nadu’s Data-Driven Approach

Tamil Nadu state has emerged as a leader in using administrative data to improve education. The state has implemented:

1. Integrated Education Management System: A unified platform that tracks student enrollment, attendance, assessments, and teacher deployment.
2. Learning Enhancement Program: The state identified specific learning gaps and developed targeted instructional materials based on assessment data.
3. School Report Cards: Simplified data presentations that help parents and communities understand school performance.
4. Block Resource Centres: Data analysis hubs that support clusters of schools in interpreting and acting on performance data.

These initiatives have contributed to Tamil Nadu consistently outperforming national averages on learning outcomes.

Gujarat’s Command and Control Center

Gujarat established an education command and control center that integrates data from multiple sources, including UDISE+, attendance monitoring systems, and assessment results. The system provides real-time dashboards for officials at different levels, enabling prompt identification of issues and intervention. School visits by officials are planned based on data indicators, prioritizing schools showing concerning patterns.

Himachal Pradesh’s School Record Digitization

Himachal Pradesh implemented a comprehensive digitization of school records, moving beyond basic UDISE+ parameters to include detailed student profiles, teacher observations, and formative assessment results. The state provided extensive training to teachers on maintaining and using these records for instructional planning. This initiative has contributed to Himachal Pradesh maintaining higher-than-average learning outcomes.

Concluding Observations

The effective use of administrative data represents a significant opportunity to improve teaching and learning in India. By strengthening data systems, building capacity for data use, and implementing data-driven practices, India can accelerate progress toward quality education for all students.

Introducing systems like SDMS offers promising avenues for individualizing education and addressing the learning crisis. However, these technical solutions must be accompanied by cultural and capacity changes that transform data from a compliance burden into a practical tool for improvement.

Several key principles should guide this work:

1. Focus on Learning: Data systems should prioritize indicators directly related to student learning, not just inputs or outputs.
2. Promote Agency: Data should empower teachers and school leaders to make informed decisions, not just monitor compliance.
3. Bridge Technical and Educational Expertise: Create mechanisms to connect MIS officers’ technical knowledge with educators’ pedagogical understanding.
4. Ensure Data Quality: Invest in improving the accuracy and reliability of school records, which form the foundation of administrative data.
5. Build capacity Systematically: Develop comprehensive programs to enhance data literacy among all educational stakeholders, from teachers to administrators.
6. Close the Feedback Loop: Establish clear protocols for acting on data findings, particularly for large-scale assessments like NAS.
7. Ensure Equity: Data analysis should highlight disparities and guide efforts to support disadvantaged students and schools.
8. Start Small: Begin with focused, high-impact data initiatives before scaling to comprehensive systems.

The path forward requires sustained commitment from policymakers, education officials, and school communities. By harnessing the power of administrative data, addressing systemic limitations, and building capacity for data use, India can transform its education system to ensure that every child achieves their full learning potential.

Suggested Readings

Aiyar, Y., & Bhattacharya, S. (2022). The post right to education act challenge: How do we ensure learning for all? Economic and Political Weekly, 57(3), 41-48.

Annual Status of Education Report (ASER). (2023). Annual Status of Education Report (Rural) 2022. ASER Centre.

Banerjee, A., Banerji, R., Berry, J., Duflo, E., Kannan, H., Mukerji, S., Shotland, M., & Walton, M. (2017). From proof of concept to scalable policies: Challenges and solutions, with an application. Journal of Economic Perspectives, 31(4), 73-102.

Bhattacharjea, S., Wadhwa, W., & Banerji, R. (2021). Inside primary schools: A study of teaching and learning in rural India. ASER Centre.

Bruns, B., Evans, D., & Luque, J. (2012). Achieving world-class education in Brazil: The next agenda. The World Bank.

Das, J., & Singh, A. (2023). Use of administrative data for improving education outcomes in low-income countries. World Development, 166, 106203.

Dewan, H., & Choudhury, S. K. (2022). The crisis of school education in India: Trends and challenges. Routledge India.

Duflo, E., Dupas, P., & Kremer, M. (2015). School governance, teacher incentives, and pupil-teacher ratios: Experimental evidence from Kenyan primary schools. Journal of Public Economics, 123, 92-110.

Ministry of Education. (2023). Implementation guidelines for Samagra Shiksha Abhiyan 2023-24. Government of India.

Muralidharan, K., Singh, A., & Ganimian, A. J. (2022). Disrupting education? Experimental evidence on technology-aided instruction in India. American Economic Review, 112(2), 310-342.

National Council of Educational Research and Training (NCERT). (2021). National Achievement Survey 2021: Report. NCERT.

Pandey, P., Goyal, S., & Sundararaman, V. (2021). Community participation in public schools: Impact of information campaigns in three Indian states. Education Economics, 29(1), 49-72.

Pritchett, L., & Beatty, A. (2015). Slow down, you’re going too fast: Matching curricula to student skill levels. International Journal of Educational Development, 40, 276-288.

Ramachandran, V., & Naorem, T. (2023). School Management Information Systems in India: Challenges and opportunities. International Journal of Educational Development, 65, 102-114.

World Bank. (2022). World Development Report 2022: Learning to realize education’s promise. The World Bank.

FAQs on Using Data to Improve Teaching and Learning in India

1. Why is data-driven decision-making important in education?

Answer: Data-driven decision-making helps identify learning gaps, allocate resources efficiently, and monitor student progress. It enables policymakers, educators, and administrators to design targeted interventions that improve learning outcomes.

2. What types of administrative data are available in India’s education system?

Answer: India collects education data through various systems, including:

• UDISEPlus: Tracks school infrastructure, enrollment, and teacher details.
• NAS: Assesses student learning outcomes at the national and state levels.
• State-Level MIS: Monitors attendance, mid-day meals, and teacher deployment.
• SDMS: Tracks individual student records and academic progress.

3. What are the main limitations of UDISEPlus?

Answer: Some key limitations include:

• Focus on infrastructure rather than learning outcomes.
• Annual data collection cycle makes real-time tracking difficult.
• Challenges in verifying data accuracy.
• Underutilization in educational planning and school-level decision-making.

4. How can the NAS survey be better utilized for improving education?

Answer: NAS can be more effective if:

• Results are followed up with specific interventions at the school level.
• Data is reported in a way that is useful for teachers and principals.
• The survey is integrated into planning under Samagra Shiksha for resource allocation.

5. How does the School Data Management System (SDMS) improve education?

Answer: SDMS tracks individual student progress, allowing teachers to:

• Provide personalized learning support.
• Detect learning difficulties early and take corrective action.
• Analyse student performance across grades for better instructional planning.

6. What are some successful global examples of data-driven education improvement?

Answer:

• Brazil’s IDEB: Uses student performance and progression rates to measure school quality.
• Chile’s SEP Program: Allocates resources based on school improvement plans.
• Vietnam’s Balanced Scorecard: Tracks leadership, teacher collaboration, and engagement.
• Kenya’s Tusome Program: Uses real-time data collection to improve reading skills.

7. How have Indian states like Tamil Nadu and Gujarat used data effectively?

Answer:

• Tamil Nadu: Integrated education data systems, school report cards, and targeted learning programs.
• Gujarat: Established a Command and Control Center for real-time education monitoring and school visits based on data indicators.

8. What structural challenges exist in India’s education data management?

Answer:

• Separation of data collection and usage, with MIS officers focusing on collection rather than analysis.
• Multiple disconnected portals leading to redundancy.
• Limited capacity of teachers and administrators to analyse and use data effectively.

9. What steps can improve the use of education data in India?

Answer:

• Train teachers and school leaders in data literacy.
• Strengthen MIS officer roles to include data analysis and educational planning.
• Ensure real-time data collection for timely interventions.
• Incorporate SDMS data into Samagra Shiksha for better decision-making.

10. How can data-driven education benefit students?

Answer: Data can help:

• Identify learning gaps and provide timely support.
• Enable personalized instruction based on student progress.
• Improve teacher training and classroom strategies.
• Ensure better allocation of resources to schools that need them the most.

Education for All in India