The document proposes models to enhance primary education in India by measuring learning outcomes and providing incentives to teachers. It suggests conducting biannual evaluations of primary school students' reading and arithmetic skills and linking teacher incentives to student performance, teacher attendance, and other factors. Implementing biometric attendance for teachers and evaluating the models through private firms could help improve accountability but may face challenges from teachers.

1. Enhancing Primary Education
in India
Team Name: Bhavishya-II
College: IIT-Bombay

2. Primary
Education
Primary
healthcare
Empowerm
ent of
women
Public
Distribution
System
Employabilit
y of youth
Agricultural
productivity
Timely
justice to all
Civic
Amenities
Research
and
innovation
Electoral
reforms in
politics
Social
welfare to
informal
sector
workersThe youth of first learners is expected to
become the enlightener of Indian future
Major fraction of India’s problems have taken
huge shape because of inability and ignorance
shown by people.
The youth of first learners is expected to
become the enlightener of Indian future.
Education empowers people with skills of
understanding, analysing and decision making.

3. Possible Concerns of Stakeholders
Government
Infrastructure
Access to quality education
Awareness about education
High Learning outcomes
Teachers
Adequate Salary
Location of posting
Parents
Safety of children
School Environment
School Proximity
Students
Interesting curriculum
Government
• 10.2% growth in density
to 3.55 schools/10 sqkm.
in last 5 years
• High Awareness:
Enrollment of 96.7%
children with 50.2% of
girls in 2012
Teachers
• Salary is 3-5 times more
than private sector
• Job security is an
additional benefit
Parents
• High enrollment
suggests that these
issues are not stopping
parents from sending
their wards to school
Students
• These problems are
inherent in the system
and need a paradigm
change in the
methodology of
imparting education
Legend:
Green = Not a major concern
Red = Major concern to be tackled first

4. Measuring the Quality of Education
• Despite spending thousands of crores on education, there is no provision to track the impact of government’s
efforts
• According to APRESt survey, infrastructure, decreasing teacher pupil ratio, high teacher salary etc. have no
correlation with learning outcomes, traditionally believed otherwise
• Hence, all our efforts have not yielded desired results
WHY?
• Mid-term evaluations to measure the learning growth and provide feedback to the teacher for motivation and
improvement scope
• End-term evaluation to assess the skills acquired and learning growth
• Making learning outcomes an explicit goal in Results Framework Document (RFD) of MHRD
• Not disclosing individual assessments in order to curb student stress
WHAT?
• State and National level committees to implement the policy in schools in their jurisdiction
• Committees to prepare a document listing out how to measure skills in the tests
• Extending contracts to private companies to conduct the tests
• Use these results for internal monitoring and assessment of the system
HOW?

5. Monitoring reading and
arithmetic skills primary
school students
A mid term evaluation to
ensure regular learning
and to provide feedback
to teachers
An end term evaluation to
measure yearly learning
growth of students
Evaluation techniques to
be decided by education
boards
Web portal to make
findings accessible to
authorities
Government can
collaborate with private
companies and NGOs to
conduct the evaluation
process
Collaboration with private
sector:
Gov. has collaborated with
TCS to provide passport to
Indian citizens resulting in
improved efficiency
Collaboration with NGOs:
NGOs like ASER, Pratham
are actively working in
this field
Average cost per student
per evaluation: ₹20
Cost per school (average
107 students): ₹2150
Yearly expense per school
(2 tests/yr): ₹4300
Other expenses: ₹700
Total yearly expense per
school: ₹5000
Total schools: 0.85 million
Total expense: ₹4.25
billion
Auxiliary expenses: ₹50
million
Total expense: ₹4.3 billion
Measuring the Quality of Education
Approximately 0.65% of the annual education budget

6. Causes Identified
High absence rate of teachers
Irresponsible Attitude of
teachers
Ineffective teaching
Lack of incentives
High Job security
Proposed Solutions
Attendance of teachers and students on start and end of daily instruction
Incentives to teachers based on performance of students, attendance and
several other factors
Biometric
Attendance
Monetary
Incentives
Substandard Education in India
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
2004-05 2005-06 2006-07 2007-08 2008-09 2009-10
Students scoring above 60% marks in grade 4th & 5th
Boys Girls
Datanotavailable
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
2008 2009 2010 2011 2012
Arithmetic skills of students of grade 5th
Substraction Division

7. Cost Estimation
total number of government schools – 8,00,000 approx.
One time installation cost – ₹ 400-500 crore.
Annual maintenance cost – ₹ 50-100 crore.
*(rough estimation of costs)
Scalability
Can be started as a pilot project in some selected districts
Expanded on the lines of cash infusion system
Biometric machines should be battery
driven keeping in mind the unavailability of
regular power in many regions.
• Average teacher absence
rate of 25% observed in
a study conducted by
APRESt
Requirement
• Will help monitor
attendance and hence in
decrease in absence rate
• Will help identify
fraudulent enrolments
Advantages
• Attendance of teachers
and students 2 times a
day
• All the data to be
collected and analysed
to generate reports at
district/state/national
level and make them
accessible through web
portal.
Implementation
• Private tender
can/should be given for
installation and
maintenance of
machines as well as for
studying data,
summarizing and
reporting.
Private Tender
Biometric Attendance

8. PROPOSED MODEL TO CALCULATE INCENTIVES
10% of annual
salary as incentive
can be given to
teachers for extra-
ordinary efforts
towards education
• 30% incentive if meet the predecided
minimum requirement
• Additional 20% incentive on extra
effort towards quality
50% weightage to end
term evaluation
performance
• 20% incentive if meet predecided
minimum requirement
20% weightage to mid
term evaluation
performance
• Incentive proportional to (actual
attendance – minimum requirement
30% weightage to
teacher’s attendance
According to APRESt survey incentive based method is 10-15 times more cost effective than
decreasing pupil- teacher ratio
Individual incentives given to a teacher is more effective than incentives given to group
Awards for the teaching excellence can be distributed to teachers for their extra-ordinary efforts
Improved teacher
attendance
Teachers teach
enthusiastically
Better Performance of
Students
Student learning
improved
Incentives to teachers
Monetary Incentives

9. •Conduction of bi-yearly evaluation process by Private firms
•Biometric attendance machine maintenance to avoid discrepancy in data
•Good performance begets bonus but there is no penalty for underperforming
•Model will not motivate teachers content with their basic pay
•Incorporation of penalty in the model would see opposition of Teacher Associations
•Measuring reading skills involve a subjective component, therefore to ensure common careful evaluation criterion
•Evaluators taking the tests should be as objective as possible
Challenges to proposed models
Transparent
Execution
No penalty
Clause
Simple
evaluation
test

10. • Karthik Muralidharan, Venkatesh Sundararaman.2011. “Teacher Performance Pay: Experimental Evidence from India”
• Karthik Muralidharan.2012. “Long-Term Effects of Teacher Performance Pay : Experimental Evidence from India”
• Karthik Muralidharan .2013. “Priorities for Primary Education Policy in India’s 12th Five-year Plan”
• Michael Kremer, Nazmul Chaudhury, F. Halsey Rogers, Karthik Muralidharan, Jeffrey Hammer. “TEACHER ABSENCE IN
INDIA: A SNAPSHOT”
• “District information System for Education” http://dise.in/AR.htm
• “RSA Animate - Changing Education Paradigms”. https://www.youtube.com/watch?v=zDZFcDGpL4U
• “Inequalities 2013: Karthik Muralidharan on Measuring Learning Trajectories with Longitudinal Data”.
https://www.youtube.com/watch?v=bkLMZKh4WBE
• “ASER”. http://www.asercentre.org/education/data/india/statistics
Bibliography