Are Children Developmentally on Track? Assessment of Age 4 Children0Preface
Early Childhood Development (ECD), which covers children aged 0-8 years, is scientifically proven as a very
sensitive period for brain development. The whole child development framework is mindful that optimal
development results from interventions in many stages of life. Yet in many settings, this period is not usually
addressed in the programs for ECD. During age 3, children move into more formal preschool settings where theeducation sector plays a dominant role. Proper learning and development environment at this age provides asolid foundation for holistic development and wellbeing of a child throughout life. Considering this, thegovernment of Nepal has developed and implemented the early learning and development standards (ELDS) forthe children of age 4 to 5 years (48-60 months). The objective of ELDS is to support children to reach age
appropriate development by providing with developmentally appropriate practices and learning environments.
Sarthak Shiksha has conducted a research aiming to explore the quality of early childhood education programsin Lalitpur Metropolitan City with reference to ELDS. In the process, data was collected from the preschool’s
children, their parents and the teachers. It was analyzed to find out the child’s development status and the key
factors influencing on their development and learning.
I am grateful to all the stakeholders who have supported us throughout the process of tool development,
enumerator’s training, tool test and administration, data analysis and report writing. I specially would like tothank Mr. Shota Hatakeyama (Michigan State University) and Kenji Kitamura (Teachers College, Columbia
University) from Sarthak Japan for their support throughout the research process from designing to reportwriting. Without them this research would not have been possible. I would also like to thank all the children,
parents, teachers, resource persons and enumerators who have contributed in this process. I am very grateful toreport writer, data analyzer, language and content editors and coordinators who brought this report in thisform. Similarly, I would like to acknowledge the collaboration and participation of Education Review Office(ERO), Ministry of Education, Science and Technology and Lalitpur Metropolitan City and thank them for theirguidance and support.
I highly appreciate Mr. Bikki Shrestha, Program officer, Sarthak Shiksha for continuous efforts to make thishappen. Finally, I would also like to extend my sincere gratitude to all the board members, general members,
advisors and Sarthak Sathis (volunteers) for their support.
I hope this research will be utilized for further improvement of early childhood education system in Lalitpur
Metropolitan City.
Meenakshi Dahal, PhD
Chairperson- Sarthak Shiksha

1

List of Abbreviations
Bikram Sambat
Demographic and Health Surveys
Early Childhood Development
Early Childhood Education
Early Learning Development Standards
Education Review OfficeGeographic Information System
Inter-Rater Reliability
Learning Corner
Multiple Indicator Cluster Survey
School Leaving Certificate
Standard Deviation
Socio-Economic Status
Socio-Emotional

BS
DHS
ECD
ECE
ELDS
ERO
GIS
IRR
LC
MICS
SLC
SD
SES
SE

2

Summary of Key findings
Characteristics of ECE facilities in Lalitpur Metropolitan City
● The number of community school ECE is less than the number of private school based ECE
and private non-school based ECE.
● In general, community school ECE were established earlier than private ECE. Community
school ECE tend to exist in old towns whereas private ECE tend to exist in new towns andsuburbs.
● Compared to private ECE, community school ECE are poorly resourced (e.g., fewer
learning corners), and their learning environments tend to be worse (e.g., larger classsize).
● Compared to private ECE, facilitators in community school ECE are relatively moreexperienced but less educated.
● Socio-Economic Status (SES) of children in community schools is lower than that in private
ECE.
● Significant social stratification is observed in ECE: Household wealth stipulates the typeand quality of ECE.

Child Development● Children from better SES households show a significantly higher degree of development inlanguage and cognitive skills, moderately better in social-emotional skills, but little
advantage in physical skills.

3

● Even after accounting for some observable characteristics of households and children,
children in private facilities show better cognitive skills but not language, physical, andsocio-emotional skills.
● Neither in-service training nor pre-service training has a positive association with childdevelopment. The contents of training for facilitators should be reconsidered.
● While the educational background of facilitators is positively associated with childdevelopment, the experience of facilitators is not. It is necessary to attract highly
educated facilitators.
● Smaller class sizes are effective for child development, but the class-size must be
sufficiently small.
● Learning environment matters. Usage of textbooks and availability of learning resources
positively associate with child development.

4

Table of Contents
1

Introduction

7

2

Methodology

9

2.1

Sample9

2.2

Questionnaire and Measurement

11

2.3

Enumerator recruitment and training

13

2.4

Data Collection

15

Distribution and Characteristics of ECE Facilities in Lalitpur Metropolitan City

17

3.1

Distribution and establishment of ECE facilities

17

3.2

Characteristics and quality of ECE facilities

19

3.3

Characteristics and quality of facilitators

21

3.4

Family characteristics by ECE facility type

22

3.5

Summary of the chapter

23

The Status of Children in ECE in the Lalitpur Metropolitan City

24

4.1

Child development status based on development standard

24

4.2

Child development and household characteristics

25

4.3

Child development and ECE type

29

4.4

What characteristics of the ECE facility associate with child development?

31

3

4

4.4.1

Methodology

31

4.4.2

Results

32

5

Conclusion

37

6

Appendix38

6.1

Appendix 1. Performance Level Description of ELDS development standards

38

6.2

Appendix 2. ELDS Cut scores for development standards

39

6.3

Appendix 3. Research Team

39

Reference

40

7

5

List of tables
Table 1 Characteristics of ECE facilities
Table 2 Characteristics of facilitators
Table 3 Family characteristics
Table 4 Children's development and household characteristics
Table 5 Children's development outcomes in a different type of ECE
Table 6 Regression of children’s development on ECE facility typeand household characteristics
Table 7 Regression of children's development on ECE facility structural quality

19
21
22
26
29
30
34

List of figures
Figure 1 Sample of ECE facilities
Figure 2 The distribution of ECE centers by typeFigure 3 Proportion of children in each developmental standard
Figure 4 HH wealth and ELDS language
Figure 5 HH wealth and ELDS cognitive
Figure 6 HH wealth and ELDS physicalFigure 7 HH wealth and ELDS SE
Figure 8 The association between class size and children's social-emotional development
Figure 9 The association between child- to- teacher ratio and children's social-emotional
development

10
18
25
27
27
28
28
35
35

6

1 Introduction
Investment in high-quality Early Childhood Education (ECE) for disadvantaged children
is indispensable to realize a prosperous and equitable society. Cases established in the UnitedStates identified three mechanisms that enable ECE to reduce poverty and inequity in society.
First, successfully implemented high-quality ECE to disadvantaged children yields a high rateof return (Heckman, 2006). Second, the positive impacts of successfully implemented highquality ECE on learning achievements are more significant among low-income children thanchildren with a wealthier background (Cascio & Schanzenbach, 2013). Third, successfully
implemented high-quality ECE has dynamic complementarity and increases the rate of return
to interventions in subsequent education levels, such as primary and secondary education(Johnson & Jackson, 2017).
As such, successfully implemented high-quality ECE can reduce poverty and inequity insociety. In fact, other low- and middle-income countries also received such benefits from ECE
expansion, and rigorous causal inference research verified it. Those countries are Jamaica(Gertler et al., 2014; Grantham-McGregor & Smith, 2016; Walker et al., 2011), Uruguay(Berlinski et al., 2008; Aguilar & Tansini, 2012), and Argentine (Berlinski et al., 2009).
However, the crucial points are "successful" and "high-quality" programs. In fact,
when the expansion of ECE is unsuccessful, even negative impacts can be observed. For
instance, in Brazil, the expansion of the ECE program brought positive impacts, but the size ofthe impact was larger among children from wealthier households than those from poor
households (Costa & Carnoy, 2015). In South Africa, the expansion of ECE does not impact
children from the bottom 60 percent of households but has a positive impact on children

7

from the top 40 percent of households. Thus, in these countries, the expansion of ECE only
exacerbates existing inequity in their society.
There are some plausible reasons, but authors of the papers point out that, due tofailure in implementation, children from wealthier backgrounds receive high-quality ECE,
while children from poor households can only receive poorly managed low-quality ECE. In
fact, cases in Bangladesh (Aboud, 2006; Moore et al., 2008) and three Eastern Africancountries (Malmberg et al., 2011) imply that high-quality ECE can bring much larger positive
impacts than normal-quality ECE.
There is not sufficient evidence concerning ECE in the case of Nepal. Thus, this study
investigates 1) what the ECE coverage is in Lalitpur metropolitan city, 2) how the quality of
ECE is in Lalitpur, and 3) how does the quality of ECE varies across children from various
backgrounds, to realize a prosperous and equitable society.
In terms of uncovering quality and equity in ECE provision, this study also pays special
attention to types of ECE. The 21st century has observed the expansion of private education
providers, and the percentage of enrollment in private institutions in pre-primary (earlychildhood education) and primary have almost doubled in the last two decades (World Bank,2019). Nepal, particularly Lalitpur metropolitan city, is not an exception. However, unlike
primary education, very little is known about the privatization of ECE in the world, except for
one study in Ghana (Pesando et al., 2020) 1. Thus, this study also aims to 4) understand what
implications the privatization of ECE has with regard to ECE quality and equity.

1

The case of Ghana indicates that private ECEs cater to children with wealthier backgrounds. Due to thisinequitable selection, children in private ECE show better development. However, once the impact of the selection iscontrolled, both private school based ECE and private non-school based ECE only to support children’sdevelopment as public ECE does. Thus, while privatization does not improve the quality of ECE, it stratifies
children based on their background and, probably, worsens social integration.

8

2 Methodology
This report focuses on Lalitpur Metropolitan City. Sarthak Shiksha coordinated withthe metropolitan city office and obtained the approval of the project.

2.1 Sample
All the ECE facilities in the metropolitan city were targeted to understand the larger
picture of the Lalitpur metropolitan city (census method). The school and ECE facilities list
provided by the municipality included 177 schools as of May 2019 counting both government
and private schools. However, nine ECE facilities on the list were not found because they
were no longer operating or had moved to different locations. Furthermore, 11 out of theremaining 168 schools that were on the list did not have ECE facilities to serve target-aged
children from 48 to 60 months.
Many ECE facilities that were not on the list (unrecognized or business registeredfacilities) were found through an informal interview with stakeholders. Thus, this study
followed Tooley and Dixon’s (2007) methodology and asked enumerators to visit every street
in the metropolitan city to find unrecognized facilities. Through this process, enumerators
found 137 unrecognized ECE facilities.
Therefore, this study aimed to include all 137 unrecognized and 157 recognized ECE
facilities in our project. 66 percent of these 294 target facilities agreed to participate in the
study. This resulted in 195 facilities, including 76 unrecognized facilities (see figure 1).
From the 195 ECE facilities that agreed to participate in the study, this study randomly
selected one target class that served target-age children, who were four-years-old (48 to 60
months) with no disabilities 2. Then, four eligible children were randomly selected from the2

There is no standardized module for measuring child development of children with disabilities.

9

target class upon the parent's agreement of participation. When there were less than four
eligible children, all the eligible children in the class were automatically selected. This
procedure resulted in 655 children.
Figure 1 Sample of ECE facilities

The selection of children from the facility was random, and thus, these children
represent all the children in the studied 195 ECE facilities. On the other hand, therepresentativeness of the facility may be limited. In particular, facilities that agreed toparticipate in the study may meaningfully differ from other facilities that did not agree toparticipate. Also, it may not be reasonable to assume that enumerators successfully found all
the unrecognized facilitators in the metropolitan city while they visited almost every street
and asked around to local stakeholders. To the extent that facilities that were not found or
did not agree to participate were meaningfully different from the studied facilities, thegeneralizability of the results will be limited. However, there is no available data that allows
us to assess any differences in facility characteristics between the studied and non-studiedgroup.

10

2.2 Questionnaire and Measurement
This study employed four modules for data collection: Early Learning Development
Standards (ELDS) assessment tool, ECE facility principal/coordinator survey, facilitator survey,
and household survey. Each module collected information on the status of child development
in five domains, facility and classroom situation, a background of facilitators, and a status ofhouseholds, respectively.
This study developed a household survey based on the Demographic and Health
Survey (DHS) and the Multiple Indicator Cluster Survey (MICS) used in Nepal. Thus, our survey
instruments are valid in the context of our project. The household survey covers a wide
variety of information regarding the target child, other household members, and the family'ssocial and economic situations. Questions for household wealth information were based on
DHS for Urban Nepal in 2016. The child functioning domain is based on questions on the MICS
6, which was developed by the Washington Group on Disability Statistics to record types anddegree of disabilities of a child.
Principal and facilitator surveys were constructed based partially on the National
Minimum Standards for ECD (DoE, 2011). The Standard covers various domains, including
physical infrastructure, health, sanitation, nutrition, security, operation, and facilitator'squalification. From this standard, we included questions regarding the classroom's structuralquality and resources that may underlie a supportive learning environment for young
children. To get more insights into classroom situations, we added questions regarding thenumber of children and facilitators, facilitator's training, and compensation to the facilitator
survey. Also, to glean information on the overall facilitator or school, we included questions
on school structure, finance, operation, and children with disabilities in the principal survey.

11Lastly, Sarthak Shiksha obtained approval for the use of the ELDS assessment toolfrom the Education Review Office (ERO). This assessment was developed by a team ofnational experts based on the Early Learning and Development Standard (DoE, 2013). Since
its development, the tool has been revised, and we used the most up-to-date version. The
tool is play-based and consists of 26 tasks with 58 subtasks to be performed by children,
covering five development domains: physical, language, cognitive, socio-emotional (SE), andcultural. For analysis, this study combined the SE domain and cultural domain as they can beconceptualized as the same construct and in order to improve upon the reliability issue
derived from the insufficient items and subtasks for the cultural domain.
Children's performance on tasks were scored by enumerators based on observations
with standardized administration and scoring procedures. Enumerators scored ‘2’ if children
performed a task correctly, ‘1’ if they performed partially correctly, and ‘0’ if they performed
incorrectly or did not respond. Domain scores were obtained by averaging over subtask
scores. When this study constructed scales (i.e., domain scores), we recorded scores from ‘2’,
‘1’,‘0’ to ‘1’, ‘.5’, ‘0’ and divide the sum of task scores by the number of tasks so that thedomain scores correspond to the percentage of subtasks that the child performed correctly,
while still taking into account the partially correct performance. Our analysis revealed thatwhile domain scores for language and cognitive domains are found to be sufficiently reliable,
physical and SE domains did not reach an acceptable level of reliability (i.e., Cronbach's Alphais below .70), one should not overly rely on the results of our analysis related to these twodomains as they were affected by somewhat large random measurement errors.
To ensure efficiency in data collection and management, Sarthak Shiksha digitalized all
the questionnaires using the Kobo toolbox. To check the validity of surveys and assessment,
this study conducted pilots. As for the ELDS assessment tool, this study paid particular
12

attention to children's understanding of expected tasks and feasibility and standardization ofassessment administration. This study conducted a pilot assessment with ten children who
were slightly over-aged (i.e., five years old) and thus not eligible for our project. While there
was no clear evidence that suggested the necessity to revise the tool itself, this study refinedsome administrative and scoring guidelines to assist enumerators in standardizing theiradministration. As for the other three surveys, we conducted pilots in two facilities with twoparents, two facilitators, and one principal from each facility. There, this study tested
whether questions were clear enough for respondents to answer without confusion andfeasibility of survey administration. Again, this study did not find any evidence on the validity
problems, but Sarthak Shiksha added some administrative and proving guidelines so thatthey would be more standardized with fewer errors.

2.3 Enumerator recruitment and training
To ensure a high-quality data collection procedure, we conducted several trainings
and assessments of enumerators. The training was mainly conducted by a program officer
from Sarthak Shiksha and another independent ECD specialist. While they were equippedwith all the assessments and surveys through their previous training, including the ELDS
training held by UNICEF in April 2019, they additionally practiced administration of all thequestionnaires. Furthermore, to ensure their ability to administrate the ELDS assessment in astandardized way, they conducted inter-rater reliability (IRR) tests. In the test, one of the
trainers administered the assessment while the other observed right behind, and both ofthem scored children's performance based on their observation. They changed their roles andconducted assessments multiple times. Through multiple IRR tests, the average agreement
between the trainers was 88 percent, with Cohen's kappa being .82.

13

Then, Sarthak Shiksha coordinated with the Home Science department of Padmakanya
Campus and several Social Work departments to recruit enumerators. For eligible applicants
who had completed their bachelor's degree, Sarthak Shiksha conducted an interview toassess their ability. In the interview, we asked about their motivation, willingness, andexperience of working with young children, their parents, and facilitators, as well as theirexperience with digital devices. For 33 candidates who passed the interview, Sarthak Shiksha
created three groups and provided six-day intensive training to each group separately. In thefirst five days, Sarthak Shiksha trained them on all surveys and assessments. In addition to
the understanding of modules, they were trained on how to administer them using digitizedquestionnaires and how to coordinate with facilities and participants. On the last day,Sarthak Shiksha conducted three types of evaluations to test their ability as a reliable
enumerator. First, Sarthak Shiksha conducted a case study-based evaluation, where
candidates recorded information on questionnaires based on scripts. Second, they took the
fidelity test for the administration of the ELDS assessment. One candidate administered ELDS
assessment with a slightly overaged child while two or three other candidates and one trainer
checked his/her fidelity on administrative and scoring procedures. Lastly, they took the IRR
test for the ELDS assessment, where a few candidates observed and scored a child's
performance while the trainer administered the assessment, and their scores were comparedwith that of the trainer. Among 33 candidates, 28 passed all the evaluations.
All of these trained enumerators showed a deep understanding of the modules, theability to communicate with children as well as adults, and followed all the standardized
administrative and scoring procedures. They had quite a high agreement in the ELDS
assessment in the IRR test. The average agreement among 28 enumerators was 93 percent,ranging from 86 percent to 98 percent. Also, the average Cohen's kappa is .87 with a range of
14

.75 and 1.00. These results of the IRR test indicate that the data collected by the enumerators
are reliable.

2.4 Data Collection
The first round of enumerators started data collection from the fourth week of July,
shortly joined by the second and third round of enumerators. A pair of enumerators visited afacility to coordinate with principals and facilitators for data collection. They explained the
purpose of the project and obtained a written form of consent from a principal. Upon theapproval of data collection from a principal, enumerators randomly selected one classroom
serving target children. They then obtained the list of eligible children in the class or createdby themselves based on information from facilitators or a principal when there was noavailable list. Using a randomization procedure with dice, enumerators randomly changed theorder of eligible children on the list and then asked a facilitator to contact the parents of
those children to record their willingness to participate. A facilitator continued to contact
parents until they either found four participants or reached the end of the list.
Then, a facilitator or principal contacted enumerators and set a date for datacollection when all participating parents came to the facility. On the day of data collection,
enumerators explained the project purpose and obtained a written form of consent fromparents, which indicated that they and their children were willing to participate in the
project. In the situation in which the parents were willing to participate but not able to cometo the facility, enumerators conducted a household survey upon oral consent through call.
The data collection took place for approximately two months through the end of
September. During this period, Sarthak Shiksha’s staff went to the field to monitor
enumerators' activities. Enumerators worked in one of three groups in assigned areas (i.e.,
the western, central, and eastern areas of the metropolitan city). The leaders of the groups
15

reported the situation of coordination with facilities and data collection on a daily basis toSarthak Shiksha’s staff. According to this report, Sarthak Shiksha’s staff checked the collected
data daily to promptly address errors. The staff had frequent meetings with group leaders tocheck the progress of data collection activity and hear the situation in the fields.

16

3 Distribution and Characteristics of ECE Facilities
in Lalitpur Metropolitan City
This chapter describes the distribution and characteristics of ECE facilities in Lalitpur
Metropolitan City.

3.1 Distribution and establishment of ECE facilities
Figure 2 below shows the location of ECE facilities in Lalitpur metropolitan city by
type. Yellow, Red, and Blue points indicate community school-based ECE centers, private
school-based ECE centers, and private non-school based ECE centers, respectively.
The locations of each type of ECE facilities have several characteristics. Regarding community
school based ECE centers, they mainly exist in old towns. Accordingly, they tend to locate
near ward offices in the Lalitpur metropolitan city. Locations of private school based ECE
centers have two tendencies. Some surround community school based ECE centers andothers are in the suburbs. Locations of private non-school based ECE centers are more or lesssimilar to those of private school-based, but they tend to locate further away from an urban
center.
Their locations imply that as city areas expanded, private school based ECE centerscatered to the ECE demand of residents of newly urbanized areas. This proposition is also
supported by their average year of establishment. Community schools have the longest
history among the three types, and their average establishment year is 2033 Bikram Sambat(BS)3. Also, those of private schools and private non-schools are 2049 BS and 2068 BS,
respectively. Thus, community schools were established to cater to residents of old towns,
and as city areas expanded, private schools responded to the ECE demand of residents there.
3

This year reflects the establishment year. Thus, the year should be different from the year school began ECE
operation.

17

After the civil war, the economic growth rate has stabilized, and more domestic migrants flew
into the city area. Private non-schools absorb the demands of these new residents of Lalitpur.
Figure 2 The distribution of ECE centers by type

Note: Yellow marks indicate community school-based facilities, red is private school-based
facilities, and blue is private non-school based facilities. The mapping is based on GIS
coordinates collected by enumerators.

18

3.2 Characteristics and quality of ECE facilities
Table 1 below displays the characteristics of ECE facilities by type.
Table 1 Characteristics of ECE facilities

Community

Class Size
Number of Facilitator (per class)Child to Facilitator Ratio
Availability of
Caretaker
Playground (Outside)
Play Hall (Inside)
Enough Play Space in Classroom
Use ofTextbook
CurriculumStandard (ELDS)
Learning Corner (LC)
Reading
Math
ScienceRole Play
Creativity
Block
Number of Subject Area LCs (SLCs)
Number of Non-Subject Area LCs (NSLC)
Subject Focus in LC (SLC>NSLC)
Note: Standard deviations in parentheses.

(N=38)
21.3 (11.5)
1.1 (.31)
19.4 (9.6)

PrivateSchool-Based(N=100)19.1 (9.6)
1.3 (.58)
15.5 (6.6)

Private NonSchool Based(N=50)
13.8 (12.1)
1.3 (.57)
10.8 (8.0)

76%
79%
53%
58%

98%
93%
63%
60%

100%
92%
84%
74%

68%
66%
79%

92%
79%
79%

78%
80%
82%

58%
74%
50%
55%
58%
68%
1.82 (1.3)
1.82 (1.2)
13%

58%
81%
69%
68%
67%
76%
2.08 (1.1)
2.11 (1.1)
19%

70%
88%
92%
80%
90%
86%
2.50 (.79)
2.56 (.81)
6%Overall, private non-school based ECE facilities are the most resourceful, community
ECE facilities are the least resourceful, and private school based ECE facilities are in-between
these two types of facilities. For instance, community facilities have a larger number ofchildren (21.3) with fewer facilitators (1.1) per class than private non-school based facilities(13.8 children and 1.3 facilitators), which subsequently lead to substantial differences in childto facilitator ratio (19.4 vs. 10.8). Private school-based facilities are in between them.
Furthermore, with a few exceptions, private non-school based facilities have moreresources than other facilities in terms of availability of caretaker, play facilities, curriculum,

19

standard, and learning corners. Although most facilities have well-balanced learning
resources, or in other words, a good balance between availability of subject area learning
corners (i.e., reading, math, science) and non-subject area learning corners (i.e., role play,creativity, and block), a larger proportion of school-based facilities (i.e., community andprivate school-based) are relatively more focused on the subject area over the non-subject
area. In particular, while only 6 percent of private non-school based facilities have more
subject areas than non-subject areas, this proportion for community and private schoolbased facilities are 13 and 19 percent, respectively.
Also, the vast majority of private school-based facilities (92%) used textbooks, thoughtextbooks are not recommended (actually discouraged) for ECE. A high proportion of facilities
use textbooks for community and private non-school based ECE facilities as well (68% and
78% respectively). Approximately 80 percent of private school-based and private non-school
based facilities have a curriculum, while only 66 percent of community facilities have one 4.
There are no differences in the proportion of facilities with the Standard (i.e., Early Learningand Development Standards) across facility types, and approximately 80 percent of facilities
have the Standard. However, one needs to be cautious of the interpretation of thesestatistics on resources. For instance, as for learning corners, curriculum, and the Standard, thesurvey questions merely ask if the facility has each of them; they do not capture how muchand how often they are utilized in practice. Also, this study finds that the types of textbooks
vary among facilities. Some of them may be more subject or academic-focused, while others
may be similar to storybooks that are recommended for use in ECE. Thus, further research isnecessary to clarify the focus of different facilities.

4

This study did not distinguish whether curriculum is government prescribed or the institution’s original one.

20

3.3 Characteristics and quality of facilitators
Table 2 below displays characteristics of ECE facilities by type.
Table 2 Characteristics of facilitators

Community

Facilitator'sAgeWorking Experience (in years)% of University or Above Education
Facilitator's training% of ECD related bachelor or master's degree% of long-term non-government pre-service (>30 days)% of short-term non-government pre-service (<=30
days)% of complete government in-service (>=30 days)% of incomplete government in-service (<30 days)% of long-term non-government in-service (>30 days)% of short-term non-government in-service (<=30 days)
Note: Standard deviations in parentheses.

(N=38)

PrivateSchoolBased(N=100)Private NonSchool
Based(N=50)

38.4 (8.1)
11.5 (6.9)
39%

32.7 (8.5)
4.4 (4.0)
43%

30.9 (7.9)
3.6 (3.2)
76%

13%
3%

4%
23%
27%

12%
30%
28%

3%
3%
16%
45%

2%
0%
18%
42%

18%
37%
26%
8%
74%

The characteristics of facilitators in community and Private ECE differ significantly.
Community facilities tended to recruit relatively less educated facilitators who remained
relatively longer. In contrast, private non-school based facilities employ relatively lessexperienced but well-educated facilitators. Private school-based facilities have relatively lessexperienced and relatively less educated facilitators.
Regarding training, while facilitators in community facilities tend to receive training
provided by the government, facilitators in private facilities are likely to receive training
provided by non-government entities. For instance, regarding pre-service training, one-fourth
to one-third of facilitators in private school-based and private non-school based facilities
have non-government training (either short-term or long-term). This proportion is lower for
facilitators in community facilities. Particularly, only three percent of community ECE
facilitators received long-term nongovernment pre-service training. In terms of government
in-service training, one-fourth to one-third of facilitators in community facilities received it.
21while few facilitators in private facilities took it. In terms of long-term non-government inservice training, few facilitators received it in general, but more facilitators in private facilities
received it than facilitators in public facilities. When it comes to short-term nongovernment
in-service training, about half of total facilitators take it, and a much larger proportion offacilitators in community facilities received it than that of those in private facilities.

3.4 Family characteristics by ECE facility type
Table 3 below shows the characteristics of the households of children across three
types of ECE facilities.
Table 3 Family characteristics

Household Characteristics

Household Wealth (in SD)
Father's Education (in Grade)
Mother's Education (in Grade)
Father Age
Mother's Age
Number of Books at Home
Parent's School Involvement
None
Minimal (once a year)
Occasional (more than once a year)
Frequent (as often as required)
Number of Household members
Number of Siblings
Average per year tuition fee of the targeted child
Note: Standard deviations in parentheses.

Community(N=132)-1.1 (.94)
5.0 (4.3)
4.3 (4.4)
32.8 (6.7)
28.5 (5.6).64 (1.4)

PrivateSchool-Based(N=351).05 (.84)
9.8 (5.0)
8.7 (5.2)
34.2 (6.0)
30.2 (4.9)
2.5 (6.0)

Private NonSchool Based(N=169).73 (.54)
13.1 (4.0)
12.6 (4.2)
36.0 (4.9)
32.3 (4.6)
7.2 (22)

6.2%
6.2%
11.5%
76.2%
3.2 (1.2)
1.0 (.93)
2642

5.0%
3.2%
6.7%
85.1%
3.1 (1.3).58 (.73)
25084

1.2%
1.8%
4.1%
92.9%
3.5 (1.6).50 (.66)
55098

Children in private non-school based ECE facilities are more likely to be from wealthierhouseholds than private school-based and community ECE facilities. The difference isespecially significant between private non-school based ECE facilities and community ECE
facilities. On average, households of children in private non-school based ECE facilities havesubstantially higher household wealth 5, higher parental education, older parents, a larger
5

The calculation for household wealth was based on the Demographic and Health Survey 2016 (Urban), which
consists of over 40 questions regarding possessions and assets. Based on these variables, this study constructed one
composite variable of family wealth using principal component analysis.

22number of household members, and a smaller number of siblings. Furthermore, householdsof children in private non-school based ECE facilities have more books at home (7.2),
compared to those in private school-based facilities (2.5) and community ECE facilities (0.6).
In addition, parents of children in private non-school based facilities tended to be slightly
more involved6 with school than parents of children in the other two types of facilities.
The average tuition fee of a targeted child also significantly differs. Households that
send their child to private non-school based facilities paid more than 20 times the tuition fees
compared to households that send their child to community facilities 7.

3.5 Summary of the chapter
Lalitpur metropolitan city has expanded its urban areas for the last few decades.
While poor-resourced community ECE facilities serve disadvantaged children in old town
areas, well-resourced private non-school based ECE facilities absorb the ECE demand ofwealthier new-town residents. The privatization of ECE is creating a different ECE systemfrom the government ones and creating stratification and segregation among children basedon their residence and wealth.
However, this stratification and segregation do not necessarily expand inequity in
Lalitpur metropolitan city because well-resourced and poorly resourced do not necessarilymean that the quality of ECE is better or worse. In the next chapter, this report displays childdevelopment status to gain insight about whether stratification and segregation expand
inequity through inequitable human capital accumulation.

6

The survey asked a question on parents’ school involvement (i.e., how frequent the parent petticoated in parentteacher meetings), based on which this study built an index ranging from 0 to 3 for parental involvement in school.
7
Tuition fee does not include other costs, such as food, AC, and transportation.

23

4 The Status of Children in ECE in
the Lalitpur Metropolitan City
This chapter analyzes the status of children in Lalitpur metropolitan city in terms of
their development outcomes in multiple domains. First, this study conducts a descriptive
analysis of the children’s development status based on three development standards:
Developmentally on track, Progressing, and Struggling. Then, this study performs anotherdescriptive analysis of children’s development outcome by household characteristics andtypes of ECE facilities. Lastly, this study analyzes the relationship between ECE facilities'
structural quality and children's development outcomes.

4.1 Child development status based on development standard
Based on children’s ELDS assessment scores, children were classified into threedevelopment standards: Developmentally on track, Progressing, and Struggling. Children in
the ‘on track’ category have achieved skills and knowledge as expected in the ELDS and are
expected to be ready for schooling without additional assistance. Progressing children fallbehind but are close to the ELDS and with support they should be able to achieve it. Lastly,
the Struggling category indicates that children fall well below the ELDS and need significant
assistance to come up to the standard.
The conceptual definition of these development standards in each domain, which iscalled the performance level descriptor (PLD), was established by ERO with support from
UNICEF. The PLD consists of statements about the knowledge, skills, and abilities of children
who would be in each standard (see Appendix. 1). Based on this conceptual definition,
children were classified into three categories using cut scores on the ELDS assessment scale,
which were developed by 20 national ECD stakeholders in a virtual workshop held by ERO
and UNICEF in 2020. See Appendix 2 for the established cut scores for each domain.
24

Figure 3 shows the proportions of children in each development standard acrossdevelopment domains. It reveals that three-quarters of the children are developmentally on
track in the language domain while half of them are on track in the cognitive and socialemotional domains. The largest developmental challenge among the studied children is thephysical domain, as only one-third of them are in the ‘On track’ category in this domain. This
information indicates that although there is a substantial proportion of children who are notdevelopmentally on track, it is possible to assist most of them in achieving expected skills andknowledge with adequate support in the cognitive, language, and social-emotional domains
because more than 80% of them are in either ‘On track’ or ‘Progressing’ categories. However,significant effort is needed to support them in the physical domain.
Figure 3 Proportion of children in each development standard

80%

73%

70%
60%

52%

50%

50%

40%

36%

35%

30%

30%
20%

34%

19%

14%

30%

17%
8%

10%
0%
Cognitive

LanguageOn track

Progressing

PhysicalSocialemotional

Struggling

4.2 Child development and household characteristics
Table 4 shows the relationship between child development and some importanthousehold characteristics. The mother's education level has an especially strong correlation
with children's development (r = .13 to .44) compared to other factors. Furthermore, parent's

25educational motivation and engagement, which are measured by their extent of school
involvement and the number of children's books at home, are also associated with most of
the developmental domains of children. Among the four domains of development, thecognitive domain was more likely to be influenced by these household characteristics, while
it seems that these factors were somewhat less influential on the physical domain.
Table 4 Children's development and household characteristics

Household Wealth
Father's Education (in Grade)
Mother's Education (in Grade)
Degree of Parent's School
Involvement
Number of Books at Home*

Language

Cognitive

PhysicalSocialEmotional

.24
.23
.30
.16

.37
.37
.44
.20

.02
.07
.13
.12

.22
.21
.32
.15

.21

.27

.16

.21

Note: Numbers in cells indicate correlation coefficients. *A few cases (9) with particularly large valueof BOOK (>20) were truncated since they seemed to be outliers.

Figures 3 through 6 visualizes the relationship between household wealth and fourdomains of children's development. They show the domain score (i.e., the % of subtasks thatthe child performed correctly) across quantiles of household wealth. They indicate thatcognitive and SE domains had a strong relationship with household wealth. In particular,children from households with the lowest 25 percent of household wealth performed 58
percent of tasks in the cognitive domain correctly, while children from households with thehighest 25 percent of household wealth performed 73 percent of such tasks correctly.

26

Figure 4 HH wealth and ELDS language

Figure 5 HH wealth and ELDS cognitive27

Figure 6 HH wealth and ELDS physicalFigure 7 HH wealth and ELDS SE

28

4.3 Child development and ECE type
Table 5 Children's development outcomes in a different type of ECE

Community
Children's Development Domain
Language
Cognitive
PhysicalSocial-Emotional(N=132)
.73
(61%)
.56
(29%)
.58
(38%)
.69
(38%)

Private SchoolBased(N=351)
.79
(72%)
.66
(50%)
.62
(38%)
.75
(51%)

Private NonSchool Based(N=169)
.83
(84%)
.74
(69%)
.62
(31%)
.81
(67%)

Note: While top values in each cell is raw ELDS assessment score, bottom values inparenthesis in each cell indicate the proportion of children who are developmentally on trackin respective domains.
Table 5 shows that there are differences in children's development outcomes between
different types of ECE facilities. In particular, children in private non-school based facilities
tended to have higher scores on the ELDS assessment than those in other types of facilities.
Such gaps are especially large between children in the community and private non-school
based facilities. Among the four development domains, a relatively large gap in score isobserved in the cognitive domain, followed by the SE domain and language domain. There isno substantial difference in the physical domain across all ECE facility types.
In terms of the proportion of children who are developmentally on track, private nonschool based facilities have the largest proportion among the three types of ECE facilities in
the language, cognitive and SE domains. The largest difference is observed in the cognitive
domain: that is, the difference in the proportion of children who are developmentally on
track in the cognitive domain between community ECE facilities and private non-school based
facilities is 40 percentage points. Less than one-third (29%) of children are developmentallyon track in the cognitive domain in community ECE facilities, suggesting the need forparticular attention in the design of appropriate interventions. Contrary, the proportion of29

children who are developmentally on track in the physical domain is smaller in private nonschool based facilities than the other two types of ECE facilities. The proportion of children
who are developmentally on track in the physical domain is very small across all types of ECE
facilities, and it suggests the necessity to pay more attention to the support for the physicaldomain of development.
Table 6 Regression of children’s development on ECE facility type and household characteristics

VARIABLESECE facility type (relative to Community
School-Based)
Private School BasedPrivate Non-School BasedHousehold Characteristics
Family wealth
Father’s education
Mother’s education
Number of child books
Parents’ school involvement (relative to
none)
Minimal (once a year)

Occasional (more than once a year)
Frequent (as often as required)
Family size
Number of siblings
Child Characteristics
Child is female
Child age
Constant

LNG

COG

PHY

SE

.040*
(.021).062**(.026).020(.021).032(.026).050**(.023).088***(.029).045(.033).034(.040).005(.007).004(.008).020**(.008).000(.000).010(.008)-.001(.009).027***(.009).000(.000).022**(.009).005(.010).030***(.010).000(.000)-.015(.012).010(.013).010(.013).001(.001)-.039(.033).008(.029).038(.024)-.000(.004)-.004(.007)-.005(.040)-.007(.035).039(.028)-.001(.005)-.003(.009)-.016(.042).042(.037).065**(.029).000(.005)-.008(.009)-.095*(.054).002(.048).028(.038).002(.007).004(.012)-.005(.009).003**(.001).462***(.067)-.002(.011).002*(.001).555***(.079).022**(.011).002(.001).497***(.083)-.024(.015).004**(.002).278**(.109)

Note: Standard errors in parentheses. *** p<.01, ** p<.05, * p<.1030

The differences in child development among different types of ECE facilities mightreflect differences in the socio-economic background of enrolled children. However, as
described in Table 6, even after accounting for some important observable characteristics ofhouseholds and children, children in private school-based facilities have significantly higher
cognitive domain scores than those in community facilities. Besides, children in private nonschool based facilities have significantly higher cognitive and SE domain scores, compared tothose in community facilities. Although further study 8 is required to have a reliableconclusion, private facilities might contribute more to better child development thancommunity facilities can do.

4.4 What characteristics of the ECE facility associate with child development?
The findings in the previous sub-chapter raise a question regarding what factors
account for differences in children's development across different types of facilities after
controlling for household characteristics. Therefore, further investigation is necessary fora potential mechanism in which different types of ECE facilities affect children's development.
To address this question, we analyze the association between characteristics of ECE facilities
and child development with further regression analysis.

4.4.1 Methodology
Based on the results from the previous sub-chapter and theoretical considerations, weselected important ECE facility factors: facilitator's training (with the seven categories),
facilitator's education, class size, child to facilitator ratio, facilitator's experience, use of
textbook, and learning resources (i.e., learning corners). We constructed three variables forthe learning corners. The first two are the number of available learning corners in the subject
8This study just accounted for observable characteristics in households and children. However, it is plausible thatsome unobservable characteristics, including the quality of parenting, lead these results.

31

area and non-subject area. We also included another variable on the subject focus, which is abinary variable that takes 1 if there were more subject area learning corners than non-subject
area learning corners, and 0 if the number of non-subject area learning corners were greaterthan or equal to the number of subject area learning corners. We also included the samefamily and child's characteristics as in table 5 to account for their influences on children's
development.
Furthermore, we included class size and child-to- facilitator ratio, and we specified
two modes based on the following consideration. If the child-to-facilitator ratio matters
because facilitators engage more sensitively with children in classes with small ratios, it islikely that up to a certain ratio, the demands of classroom management limit their ability toengage well with children. Thus, only with very small ratios can facilitators attend to children
individually. Similarly, if the effect of class size is due to improved children's engagement in
the classroom, it is possible that children feel more connected only in particularly smallclasses. Understanding whether class size and child-to-facilitator ratio are associated withchildren's development, and whether such an association is uniform over the range of classsizes and child-to-facilitator ratios is important because changes in these factors are
expensive to implement.

4.4.2 Results
The results find that there are no significant positive associations for any kind of
training with all the development domains. Although most of these associations are
insignificant, the directions these associations are negative. Furthermore, incomplete
government in-service training is significantly negatively correlated with the cognitive
domain. In other words, if facilitators have taken less than 30 days of government in-service
training (i.e., incomplete package), then on average, children performed 6 percent fewer
32

tasks correctly. However, our observational data cannot address a selection bias issue 9. Thus,
further study with experimental data is strongly demanded.
Regarding human resource management for the ECE sector, the facilitator's
experience is not significantly associated with any development domain. Thus, just having
more experience does not necessarily improve the quality of care and education thatfacilitators provide. At the same time, this relationship might be caused by selection bias 10.
Thus, further study is demanded to uncover the true relationship between the experience offacilitators and their ability. Meanwhile, their educational background is significantly
positively associated with all four domains of development. Thus, attracting an educatedlabor force to this sector can be an effective HR policy.
As for class size and child-to-facilitator ratio, the results show that there is no
significant linear association between class size and child-to-facilitator ratio and children's
development. However, both class size and child-to-facilitator ratio have larger negative
associations with children's development (especially for the SE domain) in the lower end of
the distribution. This means that the effectiveness of the reduction of class size and child-tofacilitator ratio may only emerge after a certain point at which class size becomes smallenough so that facilitators can engage in responsive and sensitive interactions with children.

9

Unskilled facilitators might take more training to compensate for their weakness. If this is the case, observational
data wrongly indicates that trainings are not associated with child development.
10
For instance, skilled facilitators might be able to change their occupation for higher wage, while the unskilled
cannot. If this is the case, only unskilled facilitators become experienced facilitators.

33

Table 7 Regression of children's development on ECE facility structural quality
VARIABLES
Facilitator's Training
ECD related degree
Long term nongovernment
PRESERT
Short term nongovernment
PRESERT
Complete government INSERTIncomplete government INSERTLong term nongovernment
INSERT
Short term nongovernment
INSERT
Facilitator's Education
University or above

LNG

COG

PHY

SE

-.015
(.028)-.002(.018)-.009(.017).027(.028)-.003(.030)-.004(.021)-.003(.016)-.044(.030)-.025(.019)-.010(.018).004(.030)-.060*(.032).011(.023).014(.017)-.063(.045)-.009(.029)-.018(.027)-.018(.045)-.040(.048).054(.034).022(.025)-.041(.031)-.007(.020)-.017(.019)-.007(.031)-.042(.032).027(.023).015(.017).036**(.016).065***(.017).064**(.025).033*(.017)-.001(.002)-.001(.009)-.000(.003).000(.009).001(.002).038*(.020)-.001(.003)-.006(.010)-.000(.003).007(.010).001(.002).039*(.021)-.004(.004)-.012(.015).001(.004).012(.015).003(.003).059*(.032)-.004*(.003)-.012(.010).003(.003).014(.010).002(.002)-.002(.022).014(.014).009(.016).037(.030).046***(.015)-.013(.017)-.024(.033).014(.023).021(.025).025(.049).019(.015).014(.017).004(.033).010(.008)-.001(.009).028***(.009).000(.000).026***(.008).004(.010).031***(.010).000(.000)-.017(.011).010(.013).007(.013).000(.001).005(.008)-.001(.010).026***(.010)-.000(.000).002(.040)-.013(.035).042(.028).000(.005)-.002(.009)-.003(.011).002(.001)-.000(.042).039(.037).072**(.029).002(.005)-.009(.009).022*(.011).001(.001)-.083(.054).005(.048).031(.039).003(.007).005(.012)-.026*(.015).003*(.002)-.001(.042).034(.038).062**(.030).001(.005)-.011(.009)-.018(.012).002(.001)Classroom Structure
slope for class size < 25slope for CFR < 9slope for class size >= 25
slope for CFR >= 9

Facilitator's experience
Use of textbook
Learning Corners (LC)
Number of an available subject
area LC
Number of available non-subject
area LC
Subject focus
Household/Child Characteristics
Family wealth
Father's education
Mother's education
Number of child books
Parents’ school involvement (relative to none)
Minimal
Occasional
Frequent
Family size
Number of siblings
Child is female
Child age

Note: Standard errors in parentheses. *** p<.01, ** p<.05, * p<.1034

Above a class size of 25 and a child-to-facilitator ratio of 9:1, the slopes for the
association with the SE domain were estimated to be close to zero, whereas the slopes below
those points were negative and significant (see figures 7 and 8 below).
Figure 8 The association between class size and children's social-emotional development

Figure 9 The association between child-to-teacher ratio and children's social-emotional development

35

Other characteristics that show significant associations with children's development
are the use of textbooks and the number of available subject area learning corners. It isinteresting that the use of textbooks is positively correlated with language, cognitive, andphysical domains but not with the SE domain. Experimental data is required to confirm if theuse of textbook does contribute to child development. It is highly likely that the usage oftextbooks just reflects unobservable characteristics that cause positive impacts on childdevelopment, including the quality of school management. Theoretically, it can enhancecognitive skills. At the same time, it might accelerate the schoolification of ECE that results innegative long-term impact. Thus, experimental data is required to conclude if education
stakeholders should promote the usage of textbooks or not. The number of available subject
area learning corners is only positively associated with the cognitive domain of development,
which is somewhat expected based on the consideration regarding the learning experienceschildren have with such learning resources. On the other hand, the number of available nonsubject area learning corners and subject focus over non-subject in learning corners are notsignificantly associated with any of the development domains.
These results of regression analysis (tables 6 and 7) imply that potential factors
underlying the difference in children's development across different types of facilities, after
controlling for household characteristics, are the facilitators’ education, class sizes and childto-facilitator ratios (especially in the lower end of the distribution), and availability oflearning resources (especially in subject area).

36

5 Conclusion
In Lalitpur Metropolitan City, while community schools serve children withdisadvantaged backgrounds and poor learning environments, private ECE facilities,
particularly non-school based ECE facilities, are well resourced and serve children fromwealthier households. Thus, the stratification of society starts from the ECE level. Without arobust redistribution mechanism in the ECE sector, inequity in this society will be further
exacerbated. One of our recommendations is to strengthen the ECE registration andmonitoring system, charge taxes for private ECE facilities that serve children from wealthierhouseholds and use the tax for community-schools. Although this policy can mitigate
inequity, segregation remains. Thus, education stakeholders may implement an affirmative
action policy to well-resourced private ECE facilities.
Even at the age of four, children from better SES households are more developed thanchildren with a disadvantaged background. Thus, parental support for the underprivileged
families before ECE is demanded.
For better HR policy for facilitators, it is worth reconsidering the contents of in-service
and pre-service government training. Further, the government may consider an introduction
to quality assurance mechanisms for non-government training. Although there is acomplementary relationship between attraction and retention, priority should be given to
attracting a more educated labor force to this sector rather than retaining facilitators.
Learning environment does matter for better child development, such as making classsize small enough and ensuring a learning corner for all ECE facilities. Thus, more resources
for this sector is demanded to implement those ECE interventions.
Our study finds that education stakeholders can strive to provide equitable, quality
early childhood education and care for children. However, as discussed in various parts of thisreport, our study has some limitations 11. Thus, further research is demanded to constructevidence informed ECE policies and interventions.

11

We appreciate the support we received from Lalitpur Metropolitan Municipality office, ERO, ECE facility staffs,
ECE experts, and enumerators. Responsibility for all errors and limitations of this study is with us.

37

6 Appendix
6.1 Appendix 1. Performance Level Description of ELDS development standards
Development Category
On track

Progressing

Struggling

On track

Progressing

Struggling

On track

Progressing

Struggling

On track

Progressing

Struggling

Performance Level Description
Cognitive domainChildren can demonstrate basic life and science knowledge, imagination andcreativity. They can recognize and classify shapes and colors, recognize andwrite basic numbers, differentiate and compare length and size of objects.
Children can demonstrate limited life and science knowledge, imagination andcreativity. They can recognize and classify shapes and colors, recognize andwrite basic numbers, differentiate and compare length and size of objects witha few mistakes.
Children have difficulties in demonstrating life and science knowledge,
imagination and creativity, recognizing and classifying shapes and colors,
recognizing and writing basic numbers, differentiating and comparing lengthand size of objects.
Language domainChildren can listen to and respond properly to familiar language, speak simple
short sentences and communicate with others, and demonstrate pre-readingand pre-writing skills.
Children can listen to and respond to familiar language with a few mistakes,
speak very short sentences and communicate with others, and demonstrate
limited pre-reading and pre-writing skills.
Children have difficulties in listening to and responding to familiar language,
speaking simple sentences and communicating with others, and demonstrating
pre-reading and pre-writing skills.
Physical domainChildren can demonstrate coordination of large muscles for whole body
movement and small muscles including hand-eye coordination. They candemonstrate health and hygiene practices.
Children can demonstrate limited coordination of large muscles for whole body
movement and small muscles including hand-eye coordination. They candemonstrate limited health and hygiene practices.
Children have difficulties in demonstrating coordination of large muscles andsmall muscles including hand-eye coordination and demonstrating health andhygiene practices.
Social emotional domainChildren can interact with peers and adults to build and maintain relationships,
demonstrate sense of self, recognize and express emotions of self and others,
respect and follow values of family, community, and nation.
Children can occasionally interact with peers and adults to build and maintainrelationships, demonstrate limited sense of self, recognize and express
emotions of self and others with an occasional difficulty, and show limited
respect to values of family, community, and nation.
Children have difficulties in interacting with peers and adults to build andmaintain relationships, demonstrating sense of self, and recognizing andexpressing emotions of self and others. They show minimal respect to values offamily, community, and nation.

38

6.2 Appendix 2. ELDS Cut scores for development standards
Cognitive
Language
PhysicalSocio-emotional/Cultural

Minimally On track
0.780
0.757
0.729
0.784

Minimally progressing
0.593
0.577
0.543
0.606

Note: Based on the Performance Level Descriptor (see appendix 1) of each category of the fourdomains, participants of the workshop conceptualized how children at the borderline of thesecategories (i.e., one between On track and Progressing (minimally on track) and another between
Progressing and Struggling (minimally progressing)) would look like. Keeping such images ofborderline children in mind, participants judged the difficulty of ELDS assessment tasks for them. Thistask-wise judgment was utilized to compute domain cut scores for two borderlines: children whose
ELDS domain score is above minimally on track cut-off scores are classified as On track group; thosewith ELDS domain scores below minimally on track cut scores and above minimally progressing cut
scores are categories as Progressing group; and children with ELDS domain scores below minimallyprogressing cut score is classified as Struggling group.

6.3 Appendix 3. Research Team6.3.1 Lead Researchers
1. Shota Hatakeyama
2. Kenji Kitamura
3. Bikki Shrestha
6.3.2. Resource Person/ Trainer
1. Sachita Suwal
6.3.3 Enumerator Leaders
1. Laxmi Thapa Chhetri
2. Rushma Adhikari
3. Sapna Poudel
4. Surekha Lawati
5. Vivek Dongol
6.3.4 Enumerators
1. Aruna Khulal
2. Babin Gurung
3. Bhawana Uprety
4. Elizabeth Gurung

5. Gazal Shrestha
6. Grishma Paneru
7. Kanchan Khatakho
8. Lali Rana
9. Maiya Basnet
10. Manju Shrestha
11. Narayani Pun
12. Nirmala Tamang
13. Poonam Byanjankar
14. Pushpa Thapa
15. Rakshya Adhikari
16. Rubina Chhusyabaga
17. Sabita Purkuti
18. Samjhana Basnet
19. Shova Bhandari
20. Shreeya Amatya
21. Shweta Bhandari
22. Sona Shahi
23. Sweta Rana

39

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42

Sarthak Shiksha
Quality Learning for All

Pulchowk, Lalitpur
www.sarthakshiksha.org
info.nepal@sarthakshiksha.org+977-1 5555678
43