Baseline Report Baseline Report
USDA McGovern-Dole International
Food for Education and Child
Nutrition Programme’s Support
(2014-2016) to WFP Laos Country
Programme
November 23, 2015
Submitted by:
Md Masud Rana
WFP Asia Project Coordinator
Kimetrica LLC
80 Garden Center, Suite A-368
Broomfield, CO 80020, USA
masud.rana@kimetrica.com
Submitted to:
Nanna Skau
Head of School Meal Programme
World Food Programme, Lao PDR
Don Nokhoum Road, Don Nokhoum
Village, Sisattanak District, Vientiane, Laos
nanna.skau@wfp.org
http://www.kimetrica.com
i
Acknowledgements
We would like to thank the World Food Programme (WFP); the Ministry of Education and Sports
(MoES); and the District Education Office staff in Lao People’s Democratic Republic (PDR) for
their time, thoughtful input, and guidance in relation to the process of conducting this baseline
survey. Without their help in sharing documents, providing insight into the history and evolution
of the School Feeding Programme (SFP) in Lao PDR, and support during the field data collection,
it would not have been possible to conduct the survey. We would also like to thank all of the in￾country stakeholders who took the time to meet with the Kimetrica team and share their candid
thoughts and reflections about the SFP.
We would also like to thank Enterprise & Development Consultants (EDC), Kimetrica’s local
partner, and its management, staff and enumerators who travelled to remote areas to access
respondents and worked tirelessly to ensure high data quality and to complete the work on
time.
We would especially like to thank WFP Washington and the regional Bureau in Bangkok for
introducing Kimetrica to the country focal points who helped us to coordinate with the United
States Department of Agriculture (USDA).
Finally, we express our thanks to USDA for their inputs in finalizing the survey instruments and
indicators that are covered by this baseline and will be used in subsequent surveys.
ii
Acronyms and Abbreviations
CLPM Correct Letters Per Minute
CWPM Correct Words Per Minute
DDS Dietary Diversity Score
EDC Enterprise & Development Consultants
EGRA Early Grade Reading Assessment
FFE Food For Education
FTF Feed the Future
FWPM Familiar Words Per Minute
IWPM Invented Words Per Minute
MGD McGovern Dole
MMS Mid-Morning Snacks
ODK Open Data Kit
ORF Oral Reading Fluency
PDR People’s Democratic Republic
PMP Performance Monitoring Plan
PPS Probability Proportional to Size
SE Standard Error
SFP School Feeding Programme
SO Strategic Objective
SRS Simple Random Sampling
TCLR Total Correct Letters Read
TFWR Total Familiar Words Read
TIWR Total Invented Words Read
USDA United States Department of Agriculture
WFP World Food Programme
iii
Table of Contents
1 Background ..............................................................................................................................4
2 Methodology............................................................................................................................6
2.1 Sampling Approach ..........................................................................................................6
2.2 Data Collection.................................................................................................................6
2.2.1 Questionnaires.............................................................................................................6
2.2.2 Implementation ...........................................................................................................7
2.2.3 Successful Completion .................................................................................................7
2.2.4 Constraints...................................................................................................................8
2.3 Data Cleaning and Analysis..............................................................................................8
3 Key Findings ...........................................................................................................................10
3.1 School Performance Indicators......................................................................................10
3.1.1 MGD SO1: Improved Literacy of School-age Children ...............................................10
3.1.2 MGD 1.1.1: More Consistent Teacher Attendance....................................................11
3.1.3 MGD 1.1.4: Increased Skills and Knowledge of Teachers..........................................11
3.1.4 MGD 1.2: Improved Attentiveness ............................................................................11
3.1.5 MGD 1.3: Improved Student Attendance ..................................................................11
3.1.6 MGD 1.3.4: Increased Student Enrolment.................................................................12
3.1.7 MGD 1.3.5: Increased Community Understanding of Benefits of Education............13
3.1.8 MGD SO2: Increased Use of Health and Dietary Practices........................................14
3.1.9 MGD 2.1: Improved knowledge of health and hygiene practices.............................15
3.1.10 MGD 2.2: Increased knowledge of safe food preparation and storage practices.15
3.2 School Variables.............................................................................................................15
3.2.1 School Facilities..........................................................................................................15
3.2.2 Food Preparation and Storage Facilities....................................................................16
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3.2.3 Teacher Training History and Background.................................................................16
4 School Feeding Attainment....................................................................................................17
5 Conclusion and Recommendations .......................................................................................18
References .....................................................................................................................................20
Annex 1: Survey Approach and Methodology ...............................................................................21
Annex 2: Sample Questionnaires...................................................................................................25
Annex 3: Baseline Values of Key Indicators, with Calculations......................................................62
Annex 4: Assessment of Literacy Level using EGRA.......................................................................69
Annex 5: Dietary Diversity Data and Analysis................................................................................78
Annex 6: Teacher Training History and Background......................................................................82
v
Figures
Figure 1: Baseline reading comprehension tier in WFP supported schools..................................10
Figure 2: Student dietary diversity scores .....................................................................................14
Figure 3: Fluency and accuracy of students at baseline ................................................................75
Figure 4: Mean reading comprehension scores against mean fluency and accuracy (number of
words correctly read by students).................................................................................................76
Figure 5: Baseline reading with comprehension tiers by intervention type .................................77
vi
Tables
Table 1: Baseline target and successful completion of individual interviews.................................8
Table 2: Change in enrolment and gender ratio over last five academic years............................13
Table 3: Number of sampled schools and households by geographical distribution and
intervention type ...........................................................................................................................22
Table 4: Tools used and types of information collected in baseline survey..................................25
Table 5: WFP Laos SFP performance indicators and their calculation by sex, geographical location
and intervention type ....................................................................................................................62
Table 6: Key school variables by geographical location (north or south) and intervention type..66
Table 7: EGRA sub-tests and their measurement approaches......................................................70
Table 8: Background demographic characteristics of EGRA pupils...............................................72
Table 9: Letter recognition subtest scores (Mean ± SE) by gender and intervention type...........73
Table 10: Familiar word reading sub-test scores (Mean ± SE) by gender and intervention type .74
Table 11: Invented word reading subtest scores (Mean ± SE) by gender and intervention type .74
Table 12: Reading fluency and accuracy subtest scores (Mean ± SE) by gender and intervention
type ................................................................................................................................................75
Table 13: Comprehension subtest scores (Mean ± SE) by gender and intervention type ............76
Table 14: Food item consumption frequencies.............................................................................79
Table 15: Consumption frequencies for the ten FTF food groups.................................................80
Table 16: Mean DDS by sex, intervention type, and province.......................................................80
Table 17: Dietary diversity status of pupils by sex and intervention type.....................................81
Table 18: Background characteristics of teacher and training history ..........................................82
1
Executive Summary
Background and Objectives
The World Food Programme (WFP) started the School Feeding Programme (SFP) in Lao People’s
Democratic Republic (PDR) in 2002. Recently, the country programme received a US$27 million
donation from the United States Department of Agriculture (USDA) to support 150,602 children
during the period 2014-2016. WFP’s school meal programme in Laos incorporates three kinds of
food supplementation: mid-morning snacks (MMS), lunch for primary school students, and take
home ration (THR) for incomplete sentence
The objective of the consultancy was to undertake a baseline survey of the Lao PDR SFP in order
to calculate USDA’s SFP performance indicators (PIs) and other school related variables across
the sampled schools. In order to do this, the baseline survey collected data on education and
food security variables at the individual, household and school levels. It also collected data on a
range of other variables including school infrastructure, school location, teacher attendance,
etc. that could potentially affect or explain programme outcomes.
Methodology
The baseline survey methodology followed a quantitative data collection approach, consisting of
a cross-sectional survey of a sub-sample of programme primary schools and beneficiaries. In
October 2015, data was collected from 85 formal schools across ten districts of six provinces
(Pongsaly, Oudomxay, Luang Namtha, Salavan, Sekong, and Attapeu). For practical and technical
reasons, the baseline team and WFP agreed to focus primary data collection in MMS (45
schools) and lunch interventions (40 schools) in primary schools. The reference period for the
school survey was the academic year 2014-15, starting in September 2014 and ending in August
2015.
From each school, ten students, ten parents, one storekeeper and one teacher were selected to
be interviewed. The response rate exceeded 95 percent. School level attendance, enrolment,
food utilisation and distribution data was collected using the school questionnaire. The parents’
questionnaire was primarily used to obtain household demographic status and student’s dietary
diversity. The pupils’ questionnaire was used to collect information on the participation in
school feeding programme and factors affecting attendance. The storekeeper and cook
questionnaire was used to assess the food storage and preparation at school level, in addition to
the knowledge and practices related to school meal preparation and distribution. The Early
Grade Reading Assessment (EGRA) test was administered to ten students from the third grade in
each school. School-level information was collected through a School Questionnaire, which
involved interviews with school principals and a review of school records.
2
Key Findings and Recommendations
Students’ literacy levels are extremely poor, with only 1.9 percent of students demonstrating at
least 75 percent comprehension compared with a target of 25 percent. To make a substantial 
progress towards the final target over the intervention period, we recommend that the SFP
develop a strong partnership with the Ministry of Education and Sports (MoES), advocating for
the use of available resources to improve the teaching and learning environment and to 
implement strategies to improve primary school pupils’ reading and comprehension skills.
Child inattentiveness is also a significant problem, with 19 percent of children being identified as
inattentive by teachers. There is an interesting gender disparity, with inattentiveness being
more common among boys (22 percent) than girls (16 percent).
Mean dietary diversity is low, at an average of 5.0 for both boys and girls. This might be due to
the programme intentionally targeting vulnerable and food insecure areas. Due to the crucial 
contributions of the community to supplement the lunch programme, we recommend working
closely with local communities and schools to strengthen this support.
Water and sanitation facilities at the school were poor. Only 44 percent of schools had access to
drinking water near or at school. Although 85 percent of schools have toilet facilities for
students, only 25 percent of schools have separate toilet facilities for girls. We recommend that
WFP work closely in partnership with the key actors to improve water and sanitation facilities, 
specifically for girls.
Facilities for food storage and preparation are generally adequate (97 percent of schools have a
dedicated store-room and 92 percent have a kitchen). However, less than half of store-keepers
(45 percent) and only one third of food preparers (33 percent) have received training on safe
food handling and hygiene practices. As a consequence, knowledge of good hygiene is poor,
with only 8.2 percent of food preparers passing a test on safe food preparation and storage
practices. We recommend increasing the coverage of safe practices training and offering
refresher courses.
This poor knowledge on health and hygiene also extends to the students. None of the students
tested obtained a passing score of 80 percent on a test on good health and hygiene practices.
Thirty-two percent of students could not identify a single good health and hygiene practice. Less
than one percent of the students could correctly identify at least 50 percent of the practices.
Reported teacher attendance appear to be high, with 94 percent average attendance and 84
percent of teachers attending at least 90 percent of the school days in the last academic year.
From the available school records, student attendance also appears to be very high, with 97
percent attendance on average and 100 percent with regular attendance (i.e. students who
attended ≥80 percent of class days). However, student attendance observed during the day of
the survey was 87 percent(see below for further findings related to school level data quality).
The discrepancy between school records and baseline attendance observations suggests that
school level record keeping and data quality is poor. In fact only 65 percent of schools had
3
complete monthly records for teacher and student attendance over the last academic year. As
both regular programme monitoring and evaluations will rely on school records, accurate record 
keeping is an important issue if the data are to be considered reliable and valid. However, WFP
has recently rolled out a new template for proper school record keeping and has strengthened
their school monitoring visits. If implemented properly, this system will improve the school level
records, resulting in more reliable and better quality data availability for the mid-term and final
evaluations. We recommend that WFP raise this critical issue of inaccurate school records at
senior level in the Ministry of Education and Sports (MoES) and continues to work closely with
the MoES, District Education Offices, and the schools to ensure compliance.
4
1 Background
Globally, more than 20 million children receive school meals from the World Food Programme
(WFP) every year (WFP, 2015). Through its school feeding programme (SFP), WFP works with
governments and development partners to support education reduce malnutrition and promote
overall development. WFP’s school meal programme in Laos incorporates three kinds of food
supplementation: mid-morning snacks (MMS) for whom ?, lunch for primary school students,
and take home ration (THR) for informal boarders0F0F0 F
1 mainly from secondary schools. Students in
MMS schools receive daily snacks consisting of 80 grammes of corn soya blend (CSB), widely
known as super cereal; 15 grammes of vitamin A fortified vegetable oil; and 15 grammes of
sugar1F1 F1 F
2
. Students in lunch schools receive 100 grammes of rice and 10 grammes of vegetable oil
on each school day throughout the school year2F2F2 F
3
. THR students receive 40 kilogrammes of rice
twice per academic year. The supplements are produced by cooks and storekeepers selected
locally by Village School Meals Committees (VSMC), and firewood and cooking water should be
contributed by the community.
Although the direct objective of school meals is to attract and keep students in school, the
indirect benefits of SFP can reach far beyond school boundaries (WFP, 2013). Indeed, one of the
SFP’s aims is to improve child literacy by increasing children’s enrolment and attendance in
schools. In addition, by emphasising girls’ education, the SFP can help to narrow the gender gap.
In addition, through the provision of a regular nutritious meal (often combined with deworming
and micronutrient fortification), the SFP aims to improve children’s nutritional status. Finally,
the SFP can have direct and indirect safety net effects, protecting children’s food security during
times of crisis and offsetting household education and food costs (WFP, 2013). However, none 
of these objectives can be achieved by the provision of school meal alone and; generally are the
effect of systematic incorporation of additional strategic programme interventions that reduce
economic, social and cultural constraints to health and learning (Finan, 2010).
WFP has maintained a country office in Lao PDR since 2000, launching the Laos SFP in
partnership with the Ministry of Education (MoE) in 2002 (WFP, 2005). During the academic
year 2014-15 WFP implemented the SFP in 1,634 schools in 32 districts within seven provinces.
In total, 1,435 schools are primary schools in which meals are offered to 142,609 children (in 90
of these schools, 1,315 children are also offered THR), and 199 are secondary schools that
provide THR to 28,145 informal boarders. In 2014, the WFP Lao PDR Country Programme
received a US$27 million donation from USDA to continue and expand upon the SFP for the
2014-15 and 2016-17 school years. With the USDA grant, WFP plans to target an average of
150,602 children in year one, 142,204 in year two, and around 113,252 children during the final
year of the programme.
 
1
Informal boarders are students who do not have access to schooling in their home villages. They are therefore living on their 
own either in school hostels or in a small hut near the school. Sometimes the informal boarders might also stay with their 
relatives near the schools.
2 The sugar is funded by the Australian government.
3 There are around 166 school days per academic year.
5
Between 2015 and 2017, WFP will gradually shift away from the MMS programme towards a
lunch programme, in an effort to align the intervention with the Government of Lao’s (GoL’s)
School Meal Policy, which will eventually enable the government to take over the programme.
During the design phase, WFP had plans to shift 200 primary schools to the lunch programme in
2015, 268 in 2016, and 300 in 2017. However, during the baseline in September 2015 the survey 
team established that WFP have identified 261 schools to move from MMS to Lunch 
intervention. Under the lunch programme, WFP provides 100 grammes of rice and 10 grammes
of vegetable oil per student per school day. Other food ingredients (e.g. vegetables, plant,
animal or animal proteins, and spices) and non-food inputs (e.g. firewood and water) are
expected to be contributed by the community. In addition to the primary school meal
programme, WFP will provide a take home ration (THR) of 40 kilogrammes of rice to informal
boarder (IB) students, predominantly from secondary schools that do not receive WFP lunches,
twice per year.
The aims of this baseline evaluation were to:
1. Present baseline values for the key WFP SFP performance indicators (PIs)
2. Determine whether these indicators vary across schools
3. Present school related variables that may be affecting variation in indicators across schools
6
2 Methodology
2.1 Sampling Approach
The baseline survey focused on quantitative data collection using a cross-sectional survey of the
programme schools and beneficiaries. This was complemented by extensive desk research
during the design phase including a review of existing programme documents. It was agreed
with WFP that the evaluation would focus only on primary schools delivering MMS or lunch to
pupils.
A total of 85 primary schools were sampled across ten districts4
3F3F3F, which spanned six provinces5
F4F4
of Lao PDR, 45 of which are implementing MMS and 40 of which have shifted to lunch
interventions. For more information on the sampling strategy, please refer to Annex 1.
In the sample, the ratio of female to male school enrolment was 0.95 (i.e. for every 100 boys
enrolled, there were 95 girls enrolled), similar to the population level enrolment ratio for all
primary schools supported by WFP in Lao PDR. The ratio of female to male programme
participation was slightly different (0.93 for MMS and 0.98 for lunch) across the two
intervention groups.
2.2 Data Collection
2.2.1 Questionnaires
The reference period for the school survey was the academic year 2014-15, which began in
September 2014 and ended in August 2015. Data collection was undertaken in October 2015.
Quantitative data was collected in each sampled school using the following seven
questionnaires (please refer to Annex 2 for samples of each questionnaire):
● The School Questionnaire was used to collect school-level information through
interviews with the head teacher, direct observation of the school facilities and data
gathered from school records.
● The Student Questionnaire was administered to a sample of ten randomly selected
pupils in each school included in the baseline survey.
● The Household Questionnaire was administered to parents of the ten randomly
selected pupils (one parent per pupil).
● The Early Grade Reading Assessment (EGRA) was administered to ten randomly
selected students from the third grade of each school (see Annex 4 for more details on
EGRA).
 
4 Phongsaly, Boontai, Hoon, Beng, Xay, Viengphoukha, Lao Ngam, Thateng, Sanxai, Sanamxai.
5 Pongsaly, Oudomxay, Luang Namtha, Salavan, Sekong, Attapeu.
7
● The Teacher Questionnaire was administered to one teacher from each school, and data
was also collected through interviews.
● The Cook Questionnaire was administered to one cook from each school, and data was
collected through interviews.
● The Storekeeper Questionnaire was administered to the person responsible for the
storage of SFP food in each school, and data collection also included direct observation
of the storeroom.
The questionnaires were developed by Kimetrica and translated into Lao. Questionnaires were
designed to inform USDA MGD school performance indicators (see Annex 3). In addition, key
student and school variables that may influence performance indicators (such as school
facilities) were collected.
2.2.2 Implementation
Enterprise & Development Consultants (EDC), a local consulting firm from Laos, pre-tested the
questionnaire in target districts and implemented the surveys under Kimetrica’s supervision. An
ODK eco-system was used for the survey and data was collected using Android powered tablets.
A combination of Kobo and Enketo Smart Paper was used to collect data using ODK Collect,
which allowed both online and offline data collection.
Data collected through tablets were directly uploaded to the server whenever a 3G or Wi-Fi
network was available. This permitted the data to be monitored on a near real-time basis by
both Kimetrica and EDC, enabling immediate feedback to the data collection team. When an
internet connection was not available, data were collected offline and uploaded when the team
returned to the district headquarters or another location with an internet connection. On a few
occasions data overload on the mobile phones meant that the enumerators had to collect data
using paper questionnaires, which were later entered into the database. The training and quality
assurance methods employed are further outlined in Annex 1.
2.2.3 Successful completion
Of the 85 selected schools, two were found to be inaccessible during the screening (verified by
MoES and WFP) and were replaced by backup schools. The response rate for students, EGRA
and parents were 100, 97 and 95 percent respectively (see Table 1). In seven schools there were
not enough grade 3 students to fulfil the EGRA quota of ten students per school. To minimise
non-response, a second household visit was made to households in which parents were not
found during the first visit. Nevertheless, the survey team was unable to reach 40 parents.
8
Table 1: Baseline target and successful completion of individual interviews
District No of
schools
Target sample
(individual)
Successful interviews conducted
Students Parents EGRA
Phongsaly 5 50 50 47 48
Boontai 6 60 60 39 60
Hoon 13 130 130 122 130
Beng 10 100 100 100 89
Xay 10 100 100 97 100
Viengphoukha 6 60 60 55 54
Lao Ngam 12 120 120 120 120
Thateng 12 120 120 120 120
Sanxai 5 50 50 50 50
Sanamxai 6 60 60 60 59
Total 85 850 850 810 830
2.2.4 Constraints
Poor availability and quality of longitudinal data due to poor record keeping at the school level
was one of the major challenges for the baseline survey team in Laos. To determine the level of
data availability at the school level (student enrolment, student and teacher attendance, and
food utilisation at school level), additional questions were added to the school questionnaire.
Almost half of the schools (48 percent) did not have any record of teacher attendance, and over 
a third (35 percent) of schools did not have any student attendance records for the previous
academic year. A quarter of the schools could not produce any enrolment records for previous
years. Overall, roughly a third of the schools could produce proper records of teacher and
student attendance, enrolment6
. The rest of the schools had only partial records available.
Availability of food utilisation data was even poorer, with around 40 percent of utilisation data
not available. Due to partial record keeping, monthly utilisation data is unreliable even for
schools with available utilisation data.
For this reason, a complete dataset was not available for all 85 schools. The actual sample size
for each of the indicators calculated is reported in Annex 3.
2.3 Data Cleaning and Analysis
During data cleaning, range and consistency checks were performed to identify outliers and to
ensure that responses were consistent with previous information. Outlying values were verified
with the field team and errors were identified.
Indicator values were calculated for all schools and were disaggregated by intervention type
(MMS or lunch) and sex (male or female). In general, school level data was not disaggregated by
province due to the small sample size. Rather, geographical differences were explored by
 
6 Overall, 35 percent of schools had complete teacher and student attendance records for the last academic year; and 34 
percent schools had proper enrolment records for previous five academic years
9
disaggregating by north and south. Where appropriate, individual level data (e.g. on parents,
pupils, EGRA) were disaggregated both by north/south and by province. The indicators
calculated from the student and household surveys were calculated by summarising all
individual samples.
10
3 Key Findings
3.1 School Performance Indicators
This section covers the main findings related to the SFP performance indicators jointly identified
by WFP and USDA (please refer to Annex 3 for detailed results presented in tabular format).
3.1.1 MGD SO1: Improved Literacy of School-age Children
Indicator 1: Percentage of students who, by the end of two grades of primary schooling,
demonstrate that they can read and understand the meaning of grade-level text
Students’ literacy levels were measured using the Literacy Boost Test developed by Save the
Children for Lao PDR, along with five sub-tests (see Annex 4 for detailed results and description
of each test). All five tests were administered to determine possible explanations for potential
low performance. Administering these tests during the baseline survey will allow programme
implementers to measure any changes in literacy levels over time as well as to investigate the
deeper causes of these changes.
Students were categorised into emergent (score of less than 50 percent), beginner (score
between 50 and 75 percent) and reader (score greater than 75 percent) based on their
comprehension sub-test score, as recommended by the Literacy Boost guidelines. As
demonstrated in Figure 1, 93 percent of students are classified as emergent and only two
percent are readers, demonstrating comprehension. These results are similar to those found by
Save the Children in a similar study (2013).
Figure 1: Baseline reading comprehension tier in WFP supported schools
This indicator does not demonstrate significant differences between groups when disaggregated
by sex and geographical location (North/South). However, there are more readers in schools
receiving MMS (2.9 percent) than in those receiving lunches (0.8 percent). Although this
difference is statistically significant, it is marginal and both are low.
11
3.1.2 MGD 1.1.1: More Consistent Teacher Attendance
Indicator 2: Average teacher attendance rates
The average teacher attendance rate over the academic year is high, at 94 percent. This is
consistent across sex and intervention type.
Indicator 3: Percent of teachers attending at least 90 percent of the school days
Eighty-four percent of teachers regularly attend school (attend more than 90 percent of school
days). This is slightly higher in schools that receive MMS (87 percent) than in lunch-only schools
(80 percent).
3.1.3 MGD 1.1.4: Increased Skills and Knowledge of Teachers
Indicator 4: Percent of teachers/educators/teaching assistants trained or certified in
teaching techniques during the last one year
Only 23 percent of the teaching staff reported having received training in teaching techniques
over the last year. This is slightly higher for female teaching staff and for those at schools
receiving MMS (both 26 percent).
Indicator 5: Percent of teachers/educators/teaching assistants in target schools who
demonstrate use of new and quality teaching techniques or tools as identified by their
supervisor/mentor/coach
The head teachers reported that all of the teachers are applying their new skillsets.
3.1.4 MGD 1.2: Improved Attentiveness
Indicator 6: Percentage of students in classrooms identified as inattentive by their
teachers
On average, 19 percent of students were classified as inattentive by two out of three of their
teachers. Inattentiveness is slightly more of a problem for boys than girls (22 percent compared
to 16 percent) and for students in schools receiving only lunch compared to MMS (26 percent
compared to 16 percent).
3.1.5 MGD 1.3: Improved Student Attendance
Complete information on monthly student attendance over the last academic year was available
from 35 percent of the schools, and an additional 16 percent of the schools had partial data on
attendance. Overall, data for only 367 students (out of 850 in the sample) were available for
indicators 7 and 8.
Student attendance was measured in in two ways:
12
1. The school attendance records of ten pupils per school for the last academic year. Both
average attendance and regular school attendance (defined as greater than or equal to 80
percent attendance) were calculated.
2. The average school attendance on the day of the survey was computed from the number
of students present at school on the day of the survey compared to the number of
students enrolled in each school. Although just a snapshot of the day, this indicator can be
used to triangulate the reliability of school records.
Indicator 7: Average student attendance
Average student attendance is high at 97 percent. It is similar for both sexes and intervention
types.
Indicator 8: Percent of students regularly attending school (at least 80 percent of the
school days)
The percent of children who regularly attended school is almost 100 percent.
Indicator 9: Student attendance on the day of the survey
School attendance on the day of the survey was lower than the average and regular attendance
rates, at 89 percent. This value is determined from all children at the schools rather than
historical information on 10 students.
3.1.6 MGD 1.3.4: Increased Student Enrolment
The baseline survey team aimed to collect enrolment data from school records for the past five
academic years in order to examine trends in student enrolment in WFP supported schools
(Table 2). Around of quarter (26 percent) of the schools could not produce any enrolment
records during the baseline survey. About 40 percent of schools had records for at least one of
the years, and 34 percent had complete enrolment records for all five years.
Indicator 9: Average percent change in school enrolment
There were only minor changes in enrolment rates between academic year 2014-15 and 
academic year 2015-16: on average, student enrolment dropped marginally, by 0.7 percent. 
However, student enrolment also declined slightly, by 2.4 percent during academic year 2014-15 
compared to the year before; and previous academic year observed less than one percent raise 
and fall in student enrolment compared to the years before. 
Indicator 10: Average enrolment ratio of girls to boys at target schools
The female to male enrolment ratio was 0.95 during academic year 2015-16, indicating that the
number of girls enrolled was 5 percent less than number of boys enrolled. There was no 
variation by school location, however, school lunch schools had better gender equity (ratio 0.98) 
compared to MMS schools (ratio 0.93), and the ratio has remained fairly consistent over the 
past four years. 
13
Table 2: Change in enrolment and gender ratio over last five academic years
Indicator 11: Average student dropout rate
The average dropout rate over the last academic year is less than one percent. It is slightly
higher for boys (1.2 percent) than for girls (0.5 percent), but the difference is not statistically
significant. Schools providing lunch interventions reported markedly higher (1.4 percent)
dropout rates than schools providing MMS (0.1 percent). However, overall, the dropout rate is
very low in the sample schools compared to the national average of 5.5 percent (UNESCO, MoES
2014). The observed differences between MMS and lunch schools and also the overall low
dropout rate might be either due to underreporting of the student dropout at school level, or to
a lower number of dropouts at sample schools.
Indicator 12: Repetition rate
Overall, 7.8 percent of students had to repeat in the same grade during last academic year. This
rate is significantly higher for boys (9.5 percent) than for girls (6.0 percent). Although MMS
school dropout rates are marginally higher (9.1 percent) than lunch schools (6.7 percent), the
difference is not statistically significant. Overall, the repetition rate in the sample schools is
slightly higher than the national average of 6.9 percent (UNESCO, MoES 2014).
3.1.7 MGD 1.3.5: Increased Community Understanding of Benefits of Education
Indicator 13: Percent of parents in programme schools who can name at least three
benefits of primary education
Less than half of the parents interviewed (45 percent) could name at least three benefits of
primary education. There is a significant difference in the parents’ understanding of educational
benefits depending on whether their child(ren) attend an MMS school (38 percent could name
three benefits) or a lunch school (53 percent). School location also affects parents’ knowledge of
educational benefits, with 42 percent in the north being able to name three compared to 50
percent in the south.
The three most common responses were that primary education: (i) improves literacy rates, (ii)
Enrolment indicators Year 
2012-13
Year 
2013-14
Year 
2014-15
Year 
2015-16
Annual percent change in student enrolment
All schools -0.4 0.6 -2.4 -0.7
MMS schools 1.4 -0.9 0.5 0.2
Lunch schools -1.7 2.0 -5.1 -1.8
Male students -1.0 -0.3 -2.6 -0.4
Female students 0.3 1.7 -2.1 -1.0
Girls : Boys enrolment ratio
All schools 0.92 0.95 0.95 0.95
MMS schools 0.85 0.88 0.92 0.93
Lunch schools 0.98 1.00 0.98 0.98
14
increases the chances of the pupil’s future self-reliance and (iii) helps to break the cycle of
poverty.
3.1.8 MGD SO2: Increased Use of Health and Dietary Practices
Indicator 14: Average dietary diversity score (DDS) of school-aged children
The quality of students’ diets was assessed in terms of dietary diversity. Following the Feed the
Future guidance (2014), the evaluation team collected complete information on all of the food
and drink consumed by each child during the 24 hours prior to the interview for 810 school
children through interviews with parents. Details on dietary diversity estimation and the main
results for this score are outlined in Annex 5.
The mean dietary diversity score (DDS) was quite low at 5.0 (out of a maximum score of 10),
which holds for both boys and girls when disaggregated by sex. It varies slightly between north
(5.2) and south (4.8); and between MMS (5.3) and lunch (4.7) schools. Both differences are
statistically significant.
Students’ food intake status was measured by categorising individual dietary diversity scores
into various classes. One categorizes DDS in terms of high, medium and low dietary diversity
scores, whereas another classifies students into two groups: those that consumed more or less
than 5 food items. As presented in Figure 2, only one in every five children exhibit high dietary
diversity. A similar proportion (22 percent) exhibit low dietary diversity. Approximately three in
five students had consumed 5 or more food groups in the 24 hours preceding the survey.
Results do not vary significantly between male and female students or between intervention
types along either method of classification.
Figure 2: Student dietary diversity scores
15
3.1.9 MGD 2.1: Improved knowledge of health and hygiene practices
Indicator 15: Percent of students in target school who achieve a passing score on a test of
good health and hygiene practices as a result of USDA assistance
None of the students obtained a passing score of 80 percent on a test on good health and
hygiene practices. While about 25 percent of students could identify at least three good health
and hygiene practices, 32 percent of students could not identify a single good health and
hygiene practice. Less than one percent of the students could correctly identify at least 50
percent of the practices.
Three most commonly identified practices were: (i) hand washing with soap after using latrine,
before eating / preparing food / feeding a child; (ii) drinking clean water from a safe source (e.g.
tube well, or treated water collected from river/lake); and (iii) keeping the school building and
compound clean.
3.1.10 MGD 2.2: Increased knowledge of safe food preparation and storage practices
Indicator 16: Percent of food preparers in target school who achieve a passing score on a
test of safe food preparation and storage practices
Eighty-five cooks from the sample schools were tested on their knowledge and attitudes
regarding safe food preparation and storage practices. Only 8 percent of food preparers
achieved at least a score of 80 percent. Results did not vary by intervention type or school
location. On average, the cooks could correctly answer five questions (out of ten); 54 percent of
the cooks answered more than 50% of the questions correctly.
3.2 School Variables
The questionnaires also recorded information on key school and student characteristics that
may indirectly affect the WFP SFP school performance indicators. A summary of the school
variables is given in Annex 3.
3.2.1 School Facilities
On average there is one teacher for every 27 students. This is worse than the national average
of 24 students per teacher in primary schools but better than the national target of 33 students
per teacher (UNESCO, MoES 2014, and NationMaster 2015). On average, there are 28 students
per classroom, also better than the national benchmark of 33 students per classroom
(Benveniste et al. 2007). Three-quarters of the schools have a library, and all of the libraries had
supplementary books for students.
Fewer than half of the schools have a source of drinking water nearby. This is slightly lower than
the national average of 56 percent of schools having a supply of drinking (UNICEF, 2014).
16
About 85 percent of schools have a toilet facility for students. This is much better than the
national average of 53 percent of primary schools with toilet facilities for students (UNICEF,
2014). However, within schools only a quarter have separate facilities for male and female
students, which means that most girls have to share a toilet with male students. Schools in the 
northern provinces have significantly better access to toilets (90 percent) compared to the 
southern provinces 77 percent. However, schools in the south were more likely to have separate 
facilities for boys and girls 41 percent) than those in the north (16 percent). 
The average distance to the nearest market is 17 km, to the nearest education office is 21 km,
and to the nearest food distribution centre is 70 km.
3.2.2 Food Preparation and Storage Facilities
Nearly all of the schools have a dedicated store-room for the food, one quarter of which were
built with USDA assistance. In 80 percent of the schools, food is stored off the ground, and
nearly all schools (92 percent) have a kitchen. On average, training in safe food preparation and
storage practices as a result of USDA assistance was 45 percent for storekeepers and 33 percent 
for food preparers. Staff in schools providing lunch are better trained (70 percent for
storekeepers and 45 percent for food preparers compared to 22 percent of storekeepers and
food prepares in MMS schools). None of the schools use smoke reducing or energy saving
stoves.
On average, only nine percent of schools have a dining area for meal consumption, though this
is higher in schools that serve lunch (40 percent). Forty-six percent of the schools reported
receiving voluntary food contributions from farmer groups, and almost 40 percent have
developed an informal partnership for food supplies.
3.2.3 Teacher Training History and Background
Information on teachers’ backgrounds and training histories was collected from 579 teachers
(57 percent female) in the 85 sample schools using the school questionnaire (see Annex 6).
Regardless of gender and intervention type, head teachers have, on average, 17 years of
teaching experience. Regular teachers have an average of 10 years of teaching experience. This
varies slightly by gender: male teachers have 12 years of teaching experience, whereas their
female colleagues have, on average, 9.5 years of experience. Teachers at MMS schools tend to
have more experience (11 years) than those at lunch schools (8.9 years). Two thirds (67 percent)
of the teachers have a technical/vocational diploma and 31 percent have a higher diploma. Less
than one percent of the teachers have a bachelor or higher level of educational qualification.
Very few of the teachers (7 percent) reported having received training on the school meal
programme. Fifteen percent reported having received training on health, hygiene and nutrition
in the last academic year.
17
4 School Feeding Attainment
Retrospective monthly information on the meals that the schools provided to the students was
explored in an effort to calculate a School Feeding Attainment (SFA) score, a measure of how
much food was prepared at the school compared to the food requirements based on student
attendance. If there was enough variation in the provision of food at the school level, the SFA
could be used to estimate and attribute the effects of the programme, if any, using a regression
analysis (for full details about the regression approach, please refer to Annex B of final
“Evaluation Plan”).
Unfortunately, the data available at school level on feeding and food utilisation at baseline was
not robust enough for a comprehensive analysis, with many missing data points due to the poor
record keeping of most schools. About half of the sample (45 schools) did not have any monthly
record of food utilisation. Of the remaining schools, even when school authorities claim to have
provided food on every school day, many had only partial data, such as records for only a few
days. This raised the question on the reliability of the data that is available and led us to
abandon the idea of conducting any impact analysis during the baseline.
18
5 Conclusion and Recommendations
The literacy comprehension of students is poor, with only 1.9 percent demonstrating greater
than 75 percent comprehension on the literacy boost questionnaire on grade level text. This
very low baseline status suggests that there is much work to be done to meet the final target of
25 percent of students (both male and female) that can read and understand grade level text.
Without any targeted measure to improve literacy through enhanced classroom instruction
methods, it will be very difficult to progress towards the final target. Targeted strategies need to 
be devised to enhance pupil’s literacy skills. Within the existing structure and resource of the 
school feeding programme it will be difficult for WFP to allocate resources for an EGRA 
intervention. Hence, we recommend that WFP builds and maintains a strong partnership with
the Ministry of Education and Sports (MoES) in order to use available resources to create a
better teaching and learning environment and to develop strategies and take actions to improve
primary school pupils’ reading and comprehension abilities.
Mean dietary diversity is low, at an average of 5.0 for both boys and girls. This might be due to
the programme intentionally targeting vulnerable and food insecure areas. MMS schools have
slightly better dietary diversity scores than lunch schools, and northern schools have higher
scores than those in the south. Community contributions can play a crucial role in improving
dietary diversity. WFP has already identified activities to encourage community contribution,
such as receiving food from farmer groups and forming partnerships with farmer groups. We
recommend working closely with local communities and schools to mobilise contributions of
food items to the school meal programme. This is particularly important for the success of the
lunch programme, as WFP only provides rice and oil, leaving the rest of the food and non-food
items dependent on community contribution.
The school level water and sanitation situation needs improvement. While toilet facilities are
generally available for students, they are not often separated by gender, and access to a safe
source of drinking water near or at school is mediocre at best. We recommend that the SFP
work closely in partnership with the key actors already identified in the results framework
(MoES, Ministry of Health, UNICEF, WHO) and other donors and non-government organisations
to improve the water and sanitation facilities at schools.
The facilities for food preparation and storage are quite good. However, there is a great need
for storekeepers and food preparers to be trained on safe practices and hygiene. We
recommend increasing training coverage and offering refresher courses in order to improve the
hygienic condition of the food served to pupils, to ensure proper stock management and to
improve the record keeping of food utilisation in schools.
Furthermore, student knowledge of good hygiene is extremely poor. We recommend WFP to 
work with the government and partners for proper implementation of activities (e.g. raising 
awareness on nutrition and hygiene, training on good health and nutrition practices, production 
19
of supplementary reading materials etc.) identified in the result framework. 
Schools in Northern provinces tend to perform better on key indicators including literacy and
dietary diversity. This may partially be explained by the fact that Northern provinces also tend to
have better school facilities, smaller class sizes, lower student dropout rates and lower
repetition rates. In addition, findings from secondary literature show that, the selected
provinces in the south (Attapeu, Salavan and Sekong) are slightly poorer than their northern
counterparts (Pongsaly, Oudomxay and Luang Namtha) (Epprecht et. al, 2008)6F6F6
7
.
School level record keeping and data quality for enrolment and food receipts are very poor.
Record keeping and maintenance must be improved to ensure that ongoing regular programme
monitoring and future evaluations are reliable and valid. WFP has recently rolled out a new
template for proper school level record keeping and has strengthened their monitoring visits to
schools. If implemented properly, this system will ensure that proper data will be available for
on-going monitoring as well as for the mid-term and final evaluations in order to analyse
programme effects. We recommend WFP to raise this critical issue of inaccurate school records 
at senior level in the Ministry of Education and Sports (MoES) and continue to work closely with 
the central, local and school level actors to ensure proper record keeping at school level.
 
7 As per a recent report by the Swiss National Centre of Competence in Research (NCCR) North-South, University of Bern, and 
International Food Policy Research Institute (IFPRI), even though poverty rate is generally higher in the northern provinces than 
in the southern provinces, in this particular sample of provinces (i.e. where WFP is implementing SFP in Lao PDR), the 
opposite is true. The report shows that headcount poverty rates in the provinces covered by the sample were: 44 percent in 
Attapeu, 55 percent in Salavan, 42 percent in Sekong, 51 percent in Pongsaly, 45 percent Oudomxay and 23 percent in Luang 
Namtha (Epprecht et. al, 2008)
20
References
Abadzi, H. (2011). Reading fluency measurements in EFA FTI partner countries: Outcomes and
improvement prospects. EFA FTI, (1). Retrieved 14 September 2015 from http://www￾wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2013/07/26/000356161_
20130726161417/Rendered/PDF/797780WP0readi0Box0379789B00PUBLIC0.pdf
Benveniste, Luis; Marshall, Jeffery; Santibañez, Lucrecia. 2007. Teaching in Lao PDR.
Washington, DC: World Bank. © World Bank.
https://openknowledge.worldbank.org/handle/10986/7710 License: CC BY 3.0 Unported
Epprecht M., Minot N., Dewina R., Messerli P., Heinimann A., 2008. The Geography of Poverty
and Inequality in the Lao PDR. Swiss National Center of Competence in Research (NCCR)
North-South, University of Bern, and International Food Policy Research Institute (IFPRI),
Bern: Geographica Bernensia
Fuchs, L. S., Fuchs, D., Hosp, M. K., & Jenkins, J. R. (2001). Oral reading fluency as an indicator of
reading competence: A theoretical, empirical, and historical analysis. Scientific Studies of
Reading, 5(3), 239–256.
Mattos L.M. (2013). Oral Reading Fluency Benchmark Procedures and Considerations: Final
Report for Save the Children. Retrieved 22 October 2015 from
readbangladesh.org/content/upload/benchmark.doc
NationMaster (2015). Laos Education Stats. Retrieved from
http://www.nationmaster.com/country-info/profiles/Laos/Education (17 November 2015)
Save the Children (2013), Literacy Boost, Lao, P.D.R Baseline Report: December 2013, Retrieved
from, http://resourcecentre.savethechildren.se/library/literacy-boost-lao-pdr-baseline￾report-2013 (17 November 2015)
UNESCO, Ministry of Education and Sports (2014), Education for All 2015 National Review
Report: Lao People’s Democratic Republic. Retrieved from
unesdoc.unesco.org/images/0023/002314/231489e.pdf (17 November 2015)
UNICEF (2014), Raising Clean Hands in Lao PDR: Joint call to action. Retrieved from
http://www.unicef.org/laos/RAISING_CLEAN_HANDS_IN_LAO_PDR_WEB.pdf (17 November
2015)
WFP (2005), World Food Programme Lao PDR: Annual Report 2005
21
Annex 1: Survey Approach and Methodology
A1.1. Sampling Strategy
A1.1.1. Sample Size Determination
The sample size was calculated considering the effect size and predictors, along with the more
widely used power and significance/probability level. Holding the power at 0.8 and probability
at 0.5 and assuming that the programme has an effect of at least 0.357F7F7F8, check 
incorporating four predictors in each model would require data from a minimum of 39
schools8F8F8F9 check for each of the interventions (MMS and lunch). However, as the
distribution of performance or impact indicator values between the programme schools was
unknown, we decided to maximise the sample size within the available budget. Feasibility and
logistical factors were also considered. The maximum sample size from both a logistical and
financial point of view was thus 85 primary schools. The sample was divided between
intervention types, with 45 primary schools receiving MMS and 40 receiving lunch.
A1.1.2. School Sampling
WFP provided information on the number of supported schools in each district along with
enrolment data and intervention types for the academic year 2015-16. As per the agreement
with WFP, it was decided to evaluate two intervention (MMS and lunch) delivered at primary
school level. So, based on this information provided, 45 schools were selected from six districts
providing MMS and another 40 schools were selected from four districts providing lunches. This
total of 85 primary schools (MMS and lunch combined) were randomly selected from ten
districts of six Provinces using a stratified multistage sampling technique. The schools within
these districts were then selected using probability proportionate to size (PPS). For the baseline,
45 MMS schools were selected from a list of 1,315 MMS school and 40 lunch school were
selected from a separate list of 261 schools providing lunch intervention. .
 
8 Sullivan, G. M., & Feinn, R. (2012). Using effect size-or why the P value is not enough. Journal of Graduate Medical 
Education, 4(3), 279–282.
9 Soper, D. S. (2013). A-priori sample size calculator for multiple regression [software]. Retrieved from 
http://www.danielsoper.com/statcalc
22
Table 3: Number of sampled schools and households by geographical distribution and intervention type
Location Province District Intervention
type
Total
no. of
schools
Total no.
of schools
in sample
Total no. of
target
households
North
Pongsaly Phongsaly MMS 52 5 50
Boontai (Boun tay) MMS 56 6 60
Oudomxay Hoon (Houn) MMS 102 13 130
Xay MMS 84 10 100
Beng Lunch 68 10 100
Luang
Namtha Viengphouka-Done Lunch 46 6 60
South
Attapeu Sanxai MMS 37 5 50
Sanamxai MMS 40 6 60
Salavan Lao Ngam Lunch 63 12 120
Sekong Thateng Lunch 51 12 120
Total 85 850
A1.1.3. Sampling of Students and Their Families
In each primary school, a total of ten pupils were selected from grades one to five for interviews
using simple random sampling (SRS). The selected students’ parents (or close relatives of the
parents) were included for the household interview. Another ten students were selected from
grade three for EGRA using the same SRS process. The procedure is detailed below, with the
sampling unit being the whole school for the sample of ten students and only grade 3 for the
EGRA:
● If available, the student register was obtained from each classroom or from the school
principal; otherwise the total number of students in the class was counted.
● Sampling difference was defined as the number of students to be interviewed (in our
case, ten were to be selected from third grade for EGRA).
● A random number was selected between one and the sample difference using a random
number table.
● This figure was then used to count from the class lists and select each “X”th student to
be part of the sample.
● If a student was absent or refused to participate, the next number on the class list was
selected. If that student was absent or refused, the following number was selected. This
provided the sample of ten students distributed across the school/grade 3 class. The
number of refusals and absences in the school report were recorded.
● Students were pulled out from their classes in small groups, one student per
enumerator, in order to minimize class disruption.
23
A1.2. Training and Quality Assurance
A1.2.1. Training
Enumerator training was conducted in three phases. In first phase, the local survey firm was
provided with the draft questionnaire and draft enumerator guide in order to check if the
questionnaire was contextually appropriate and to familiarize the enumerators with the general
questions.
In the second phase, the enumerators and supervisors were introduced to the digital version of
the questionnaire and taught how to navigate through it, review and edit responses, and upload
the finalised form. An expert from Kimetrica provided a three-day, hands on training to the
team in Laos to confirm that they were comfortable with the system.
Finally, a five-day training was conducted with 24 enumerators and supervisors during the last
week of September 2015. The final training covered both the paper and digital versions of the
finalised questionnaire and ensured that all of the enumerators were competent in interviewing
and observation skills. Kimetrica’s project coordinator provided necessary clarification as to the
objective of the survey and what each of the questionnaires were designed to measure.
A1.2.2. Quality Control Mechanisms
Data quality was assured through intensive enumerator training and maintenance of a strict
data collection protocol. The baseline survey team ensured the accuracy, validity and reliability
of the survey data by employing various quality assurance mechanisms at every stage of the
baseline survey, as outlined below:
● Direct monitoring by Kimetrica: The whole data collection process was directly
monitored by the survey manager to ensure that the local survey firm was following the
agreed quality control steps. The survey manager maintained a presence in the field
throughout the data collection period, actively taking part in training enumerators and
pre-testing the questionnaire. Kimetrica’s project coordinator also visited during the first
week of data collection and to monitor the progress and quality.
● Recruitment of qualified enumerators and supervisors: EDC recruited experienced and
trusted enumerators. Those with previous experience in collecting data using mobile
phones/tablets and working in SFP evaluation were given preference.
● Direct observation: A team of supervisors was selected to observe interviews and
provide feedback on training techniques. Kimetrica’s survey manager provided guidance
on how to observe interviews and report on interview observation. The survey manager
also participated in direct observation and provided feedback.
● Re-interviewing: The survey manager re-interviewed a sample of the respondents in
order to validate the accuracy of the data collected.
● Non-response: Every effort was made to avoid non-response. Schools were not
informed of the survey in advance to avoid data fabrication. However, the data
collection team, with the support from District Education Offices and WFP local staff,
24
prepared the survey schedule in such a way that the schools would be in session when
they were visited. At the household level, efforts were made to ensure that the data
collection team revisited households in which parents could not be reached on the first
day. Supervisors kept track of all pending interviews using survey control sheets and sent
enumerators back later to complete data collection.
● Cross-checking: Every questionnaire was cross-checked by other team members and/or
supervisors prior to being uploaded.
● Logical and consistency checking: As data was collected using android tablets, logical
and consistency checks were put in place to minimise human error. Uploaded data was
regularly reviewed by the survey manager to check for consistency.
25
Annex 2: Sample Questionnaires
The seven data collection tools are summarised in Table 4.
Table 4: Tools used and types of information collected in baseline survey
Tools used Types of information collected
School Questionnaire School enrolment, attendance, and dropout rates; teachers’ academic
qualifications, training, and attendance; school building and facilities;
school-level food delivery, utilisation and stock management.
Student Questionnaire Pupil participation in the school feeding programme; eating practices;
factors affecting school attendance and performance.
Household Questionnaire Household level information on demographic composition, level of
education, school participation, occupation, employment and income;
individual level dietary intake data from 24-hour recall; participation in
the school feeding program.
Early Grade Reading
Assessment (EGRA)
Letter recognition, familiar word reading, invented word decoding, oral
reading fluency and comprehension; major factors affecting reading and
comprehension skills of early grade students.
Teacher Questionnaire Teachers’ socio-economic status, training history, teaching techniques
and participation in school feeding programme.
Cook Questionnaire Cooks’ knowledge, attitudes, and practices with regards to health,
hygiene, and nutrition.
Storekeeper Questionnaire Commodity stock management; and availability, quality and
maintenance of storage facility.
Complete questionnaires are provided on the following pages.
26
School Questionnaire
USDA McGovern Dole, Australian Aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Section 1: Interview detail
# Question Response Code
SCQ 101 Province
SCQ 102 District
SCQ 103 School Name
SCQ 103_A School Code This code should be auto generated by the
tablet programme.
SCQ 105 Latitude
SCQ 106 Longitude
SCQ 107 Respondent name
SCQ 108 Can we please have your
contact number?
(either telephone/cell phone
number. if available mobile
number is preferred)
SCQ 109 What is your role in this school?
___
1. Head Teacher/Principal (skip to SCQ 111)
2. Deputy Head Teacher /Principal
3. Teacher
4. Administrative officer
5. Other (specify)
SCQ 110 Director/Head Master’s name
(only if Respondent is not the
Head Teacher)
SCQ 111 What is the school ownership
type?
___
1. Government Primary School
2. Registered Non-Government Primary
School
3. Government Secondary School
4. Registered Non-Government Secondary
School
5 Religious school (primary/pre-primary)
6. Religious school (secondary)
7. Community/ NGO Primary School
8. Community/ NGO pre-primary School
9. Others (specify)
SCQ 112 What is the school category
(gender)?
___
1. Boys School
2. Girls School
3. Mixed gender School
27
SCQ 113 Date of the Interview
____/____/____
Day/Month/Year (e.g. 15 / 04 / 2015)
SCQ 114 Supervisor Code
SCQ 115 Supervisor Name
SCQ 116 Enumerator Code Please add code of supervisor in
SCQ 117 Enumerator Name Please add name of supervisor in
Section 2: School Feeding Program
Question Response Code
SCQ 201 From when this school is receiving
support from the School Feeding
Programme (WFP/Government)?
(This question encompasses any
component of the school feeding
programme starting from September
2014. This is to assess how many
months before the baseline they
started intervention)
_______ _______
Years Months
Put “99” for years and Months, if the
school have not received any support yet,
but will receive (skip to SCQ203)
SCQ 202 What type of support did your school
receive (or currently receiving) from
the School Feeding Programme /
School Meal programme?
(Ask the Headmaster about all the
options mentioned here, and at the
also check if there is any additional
support)
(Circle all that apply)
1. Snacks (Mid-Morning Snacks) for the students
2. Lunch (Cooked Lunch) for students
3. Meals for teachers / support staff
4. Take Home Ration for students
5. Rations for teachers
6. Rations / CASH for support staff / Cook / Storekeeper
7. Cash for buying Vegetables and Fruits
8. Textbooks
9. Other print materials (i.e. supplementary books for students)
10. school gardening support
11. Infrastructure support (kitchen/toilet/store room etc.)
12. Water supply / tippy tap
13. Training for teachers / administrators / support staff
14. Training for students / parents / others
15. Teaching materials / guidelines
16. other (specify)
SCQ 203 What are the avenues or
communication channels through
which parents and pupils get
information about School Meal
Programme or make complaints
about the programme?
(Circle all that apply)
1. None
2. Regular formal / planned meetings with Village Education
Development Committee (VEDC)
3. Regular meetings with School Administrators
4. Suggestion Box
5. Helpline
6. Informal communication (verbal) with teachers / VEDC
members
7. Don’t know / refuse to answer
8. Other (specify)________
SCQ 204 Does the school have a Village
Education Development Committee
(VEDC)?
____
1. Yes
2. No (SKIP to 210)
28
SCQ 205 How many members does the Village
Education Development Committee
(VEDC)) have?
Total number of VEDC members
SCQ 206 How many female members does the
Village Education Development
Committee (VEDC) have?
Number of Female VEDC members
SCQ 207 What is the level of participation and
engagement of the Village Education
Development Committee (VEDC) in
the School Feeding Programme (SFP?
____
1. High
2. Medium
3. Low
SCQ 208 What is the level of participation and
engagement of the Village Education
Development Committee (VEDC) C in
other aspects of school management?
____
1. High
2. Medium
3. Low
SCQ 209 Did the Village Education
Development Committee (VEDC
members receive any training
intervention from WFP?
1. Yes
2. No
3. Don’t know
SCQ 210 What is the distance by road (km) to
the nearest food market
(regular/permanent market) from the
school?
Put “999” if there is a market but distance
in Km is not known (Skip to SCQ 211)
Put “888” if there is no permanent market
SCQ
210A
What is the What is the distance by
road (km) to the nearest trade fair
(irregular temporary market) from the
school?
Kilometers
SCQ 211 How long does it take to go to the
nearest food market
(regular/permanent market) from the
school?
Number of minutes
SCQ 212 What is the distance by road (Km)
from school to the nearest
educational office?
Kilometers
SCQ 213 What is the distance by road (Km)
from school to the food distribution
center / Warehouse? (Approximate
distance in Km)
Kilometers
SCQ 214 Does the school buy food items (e.g.
corns, rice, vegetable, fruits) from
local farmers / farmer’s group for
students (for school meal)?
1. Yes
2. No
SCQ 215 Does the school get voluntary
contributions of food items from
farmers/ farmers groups for students
(for school meal)?
1. Yes
2. No
SCQ 216 Does the school have any formal /
informal partnership with Farmer’s
group?
1. Yes
2. No (Skip to SCQ 217_A)
SCQ 217 How many farmer’s groups does the
school have partnership with? Number of partnership
SCQ
217_A
Does the school have a vegetable
garden?
1. Yes
2. No
29
SCQ 218. Non-food contribution
# Non-food item contribution by
School/Parents
Contributed
during academic
year 2014-15?
1. Yes
2. No (go to Next)
Who Contributed?
1. School
2. Parents
3. External Donors
4. Combination (specify)
Approximate % of
requirement met.
1. More than 100%
2. 100%
3. 50%
4. 25%
5. 10%
6. <10%
SCQ 218_1 SCQ 218_2 SCQ 218_3 SCQ 218_4
1 Water
2 Firewood
3 Cooking Utensils
4 Cleaning Products
5 Plates and cutlery for pupils
6 Cooks Salary
7 Volunteering as cook
8 Storekeeper Salary
9 Labor for construction/
rehabilitation of kitchens
10 Labor for construction/
rehabilitation of storage rooms
11 Labor for construction/
rehabilitation of dining area for
the children
12 Timber for construction/
rehabilitation of kitchen/storage
room
13 Other (specify)_____________
Section 3. School Facilities
Question Response Code
SCQ 301 Number of classrooms
________
SCQ 302 Does the school have a Library or a place
where books are stored? ________
1. Yes
2. No (go to SCQ 304)
SCQ 303 If yes, how many supplementary books does
the school have? ________ Number of supplementary book
SCQ 304 Does your school have a storage room/facility
to store food items?
1. Yes
2. No
30
SCQ 305 If not, where is the food stored? 1. In a class room
2. In teacher’s room
3. In the kitchen
4. Open space
5. Other (specify)
SCQ 306 Is the food stored off the ground? 1. Yes
2. No
SCQ 307 Does your school use raised wooden pallets for
commodities' storage (i.e. store food items off
the ground)?
1. Yes
2. No
SCQ 308 Does your school have a kitchen?
________
1. Yes
2. No
SCQ 309 If not, where is the food normally prepared?
________
1. In a classroom
2. Open space / School yard
3. Other
SCQ 310 Does your school use smoke reducing/Energy
saving stoves? ________
1. Yes
2. No
SCQ 311 Does the school have a dining area for the
school meals
1. Yes
2. No
SCQ 312 Does the school have a source of drinking
water for students near or at school?
1. Yes (SKIP to SCQ 312B)
2. No
SCQ 312A If NO, how does the students get drinking
water during school hours?
(Multiple Response)
1 Buy Bottled water from shops
2. Children carry water from
home
3. Get water from neighbours
4. Other (Specify)
SCQ 312B If YES, What is the main source of DRINKING
water? (single response)
________
1. Piped water into dwelling, plot,
or yard
2. Public tap/standpipe
3. Tube well/borehole
4. Protected dug well
5. Protected spring
6. Rainwater collection
7. Unprotected spring
8. Cart with small tank/drum
9. Tanker truck
10 Surface water (river, dam,
lake, pond, stream, canal, or
irrigation channel)
11. Other (Specify)
SCQ 313 How many classrooms have been rehabilitated
/ constructed with WFP/USDA support? (from
August 2014 till now)
Put number of classrooms
rehabilitated / constructed
Put “0” if none
SCQ 314 How many kitchens has been rehabilitated /
constructed with WFP/USDA support?
(from August 2014 till now)
Put number of Kitchens
rehabilitated / constructed
Put “0” if none
SCQ 314A Did your school receive any Smoke reducing/
Energy Saving Stove from WFP/USDA in last
one year?
1. Yes
2. No
SCQ 315 How many storage rooms has been
rehabilitated / constructed with WFP/USDA
support? (from August 2014 till now)
Put number of Store rooms
rehabilitated / constructed
Put “0” if none
31
SCQ 316 How many wells and water stations/systems
has been rehabilitated / constructed with
WFP/support? (from August 2014 till now)
Put number of toilets
rehabilitated / constructed
Put “0” if none
SCQ 317 Does the school have toilets for the students?
ONLY FOR OBSERVATION
________
1. Yes
2. No (Skip to section 4)
SCQ 318 How many toilets have hand washing facilities
within or nearby?
ONLY FOR OBSERVATION
________
Put number of toilets with hand
washing facilities. Put “0” if none
of the toilets have hand washing
facilities.
SCQ319 Do female students have separate toilets from
male students?
ONLY FOR OBSERVATION
________
1. Yes
2. No
#
What type of toilet does the school have Does your school
‘have this type of
toilet?
1. Yes
2. No (go to next
type)
Number of
boys’ toilets
Number of
girls’ toilets
Number
of mixed
toilets
SCQ 320 SCQ 321 SCQ 322 SCQ 323 SCQ 324
1
Flush or pour/flush facilities connected to
a: (Piped sewer, septic, pit latrine)
2
Flush or pour/flush toilets without a
sewer connection
3 Pit latrines with a slab
4 Pit latrines without slab/open pit
5 Ventilated improved pit latrines
6 Composting toilets
7 Bucket latrines
8 Hanging toilets/latrines
9
Latrine out of order
32
Section 4: Teacher-Head Teacher
Teacher
ID
Teacher’s Name
(start with Head
teacher’s
information)
Sex
1. Male
2. Female
Age
(yr)
Educational
Qualificatio
n
1. MSc or
higher
2. Bachelor
3. Higher
Diploma
4. Technical/
Vocational
Diploma
5. Higher
Secondary
6. Secondary
7. Primary
8. Informal
Education
9. Other
(Specify)
Position in the school
1. Head teacher/
principal
2. Deputy head teacher
3. Teacher (permanent/
regular)
4. Teacher (paid but
temporary)
5. Teacher (volunteer
without pay)
6. Other (specify)
Years
of
teachi
ng
experi
ence
Years
of
experi
ence
in
their
curren
t role
(e.g.
as a
head
teach
er /
senior
teach
er ,
etc. )
Full
time
/
Part
time
1.
Full￾time
2.
Part
-
time
Teachers training history
(in last 1 year)
1. Yes; 2. No
Use of training
(teaching)received
(1. Yes; 2. No)
safe food preparation and storage
practices
Commodity Management
Teaching / Learning techniques (at least 2
days or 16 hours)
Training related to lunch and snack
programme
Health hygiene and nutrition
If trained, does s/he demonstrate use of new
and quality teaching techniques or
If trained, does s/he demonstrate
improved literacy instruction identified by
his / her supervisor/ head teacher
If trained, whether the teacher is using
technique of commodity management
and keeping records?
SCQ
401
SCQ 402 SCQ 403 SCQ
404
SCQ 405 SCQ 406 SCQ
407
SCQ
408
SCQ
409
SCQ
410
SCQ
411
SCQ
412
SCQ
413
SCQ
414
SCQ
415_1
SCQ415
_2
SCQ415
_3
1
33
SCQ 400A Does the school have record of teacher attendance for last academic year? 1. Yes full record
2. Yes, but partial record
3. No record found at school
SCQ 400B Does the District Education Office have record of teacher attendance for last academic year? 1. Yes full record by month
2. Yes, but partial record by month
3. Yes, only annual attendance
4. No record found
SCQ 400C Is the data available from either school / district education office record? 1. Yes
2. No (SKIP whole Teacher Attendance)
SCQ 400D If yes, which data source is used to fill up the teacher attendance history? 1. Official record from School
2. Official record from District Edu. Office
3. Mixed / Both
Teacher
ID
Name of the Teacher
(Optional)
Sex
1. Male
2. Female
Teacher Attendance History
(Put the number of days he/she attended school. Put 88, if data is not available and 99 if not applicable, i.e. if he / she
was not working in that certain month)
Sept
2014
Oct
2014
Nov
2014
Dec
2014
Jan
2015
Feb
2015
Mar
2015
Apr
2015
May
2015
Jun
2015
Jul
2015
Aug
2015
Sep
2015
Q416A Q416B Q417 Q418 Q419 Q420 Q421 Q422 Q423 Q424 Q425 Q426 Q427 Q428 Q429
34
Section 5: Observation School Survey
# Grade of students
Enrollment (current academic year,
i.e. 2015-16)
Total number of students present on
the survey day (head count)
Male Female Male Female
SCQ 501 SCQ 502 SCQ 503 SCQ 504 SCQ 505
1 Primary Grade - 1
2 Primary Grade -2
3 Primary Grade -3
4 Primary Grade -4
5 Primary Grade -5
6 Secondary
Observation RECORD
SCQ 506 Teachers present in school during survey
(FROM OBSERVATION)
SCQ 507
How many teachers eat lunch with food coming from the same pot
used to feed the pupils?
(FROM OBSERVATION)
The enumerator weighs commodities cooked on each school survey day
(distinguish between commodities provided by WFP and by
School/Parent contribution)
(Kilograms)
No. Items
Observation, Measure & Record
WFP School/Parents Other, sources
SCQ 508 SCQ 509 SCQ 509A
1 Rice
2 Flour (Corn Soya Blend / CSB)
3 Oil (vitamin A fortified) - liter
4 Sugar
5 Meat (animal Flesh)
6 Organ Meat (liver, kidney etc.)
7 Fish
8 Eggs (pcs)
9 Milk (liter)
10 Vegetables
11 Fruits
12 Condiments
13 Others
35
No Non-food item contribution by School/Parents
Observation record
1. Yes ; 2. No
SCQ 510
1 Water
2 Firewood
3 Cooking Utensils
4 Cleaning Products
5 Plates and cutlery for pupils
6 Cooks Salary
7 Volunteering as cook
8 Storekeeper Salary
9 Labor for construction/ rehabilitation of kitchens
10 Labor for construction/ rehabilitation of storage rooms
11 Labor for construction/ rehabilitation of dining area for the children
12 Timber for construction/ rehabilitation of kitchen/storage room
13 Other (specify)_____________
36
SCQ
600A
Does the school have record of Student Enrolment for
past academic years?
1. Yes full record for past 5 years
2. Yes only for last academic year
3. No record found at school
SCQ
600B
Does the District Education Office have record of student
enrolment for past academic years?
1. Yes full record for past 5 years
2. Yes only for last academic year
3. No record found
SCQ
600C
Is the data available from either school / district
education office record?
1. Yes
2. No (SKIP whole section 6)
SCQ
600D
If YES, which data source is used to fill up the student
enrolment history?
1. Official record from School
2. Official record from District Edu. Office
3. Mixed / Both
Student
Code
Student name
(All sampled students)
Sex
(1=Male;
2=Female)
According to the teachers, is he/she
generally attentive in the class?
(1. Yes; 2. No; 99. Not applicable/no more
teacher)
Measure the food the child
have received as mid￾morning snacks / Lunch
(Grams)
Opinion of
Teacher 1
Opinion of
Teacher 2
Opinion of
Teacher 3
Measurement Record
SCQ511 SCQ512 SCQ513 SCQ514 SCQ515 SCQ516
37
Section 6: School record (teachers & Students)
# Academic
year
Total number of students
(ENROLLMENT)
“put 999 if data not available”
Number of students promoted to next
class (PASSED)
“put 999 if data not available”
Number of students remaining at the
same class (REPETIATION)
“put 999 if data not available”
Number of students
discontinuing studies
(DROPOUT)
“put 999 if data not
available”
Pre-Primary Primary Pre-Primary Primary Pre-Primary Primary Pre-Primary Primary
SCQ601
Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls
SCQ 602 SCQ 603 SCQ 604 SCQ 605 SCQ 606 SCQ 607 SCQ 608 SCQ 609 SCQ 610 SCQ 611 SCQ 612 SCQ
613
SCQ
614
SCQ
615
SCQ
616
SCQ
617
1 2014-15
2 2013-14
3 2012-13
4 2011-12
5 2010-11
Section 7: Attendance Record; Record of school days (working days and holidays)
# Months Total Number of
School Days
Off days (Public
Holidays / Weekends )
Seasonal closure due to weather / Local festival or any other reason decided by District
education office / National Government)
SCQ701 SCQ702 SCQ703 SCQ704
1 September 2014
2 October 2014
3 November 2014
4 December 2014
5 January 2015
6 February 2015
7 March 2015
8 April 2015
9 May 2015
10 June 2015
11 July 2015
12 August 2015
13 September 2015
38
SCQ
700A
Does the school have record of Student attendance for last academic year? 1. Yes full record
2. Yes, but partial record
3. No record found at school
SCQ
700B
Does the District Education Office have record of student attendance for last academic year? 1. Yes full record by month
2. Yes, but partial record by month
3. Yes, only annual attendance
4. No record found
SCQ
700C
Is the data available from either school / district education office record? 1. Yes
2. No (SKIP whole student Attendance)
SCQ
700D
If YES, which data source is used to fill up the student attendance history? 1. Official record from School
2. Official record from District Edu. Office
3. Mixed / Both
# Student
code
Sex
(1=Male;
2=Female)
Student Grade
(1 = Grade 1; 2 =
Grade 2; 3 = Grade
3; 4 = Grade 4; 5 =
Grade 5)
Student attendance and school days missed (collected from school record)
(Put the number of days he/she attended school. Put 88 if data is not available and 99 if not applicable, i.e. if he / she was
not enrolled in this school)
Sept
2014
Oct
2014
Nov
2014
Dec
2014
Jan
2015
Feb
2015
Mar
2015
Apr
2015
May
2015
Jun
2015
Jul
2015
Aug
2015
Sept
2015
SCQ 705 SCQ 706 SCQ 707 SCQ
708
SCQ
709
SCQ
710
SCQ
711
SCQ
712
SCQ
713
SCQ
714
SCQ
715
SCQ
716
SCQ
717
SCQ
718
SCQ
719
SCQ
720
1
2
3
4
5
6
7
8
9
10
SCQ 800 What is the source of information for food utilization at school level? 1. Record filled up by school and kept at school
2. Record fill up by schools but given to WFP
3. District Education Office
39
Section 8: Food utilization history
SL Months Number of students enrolled Number of students receiving daily school meals/snacks Student attendance
(cumulative
attendance
number)
Total
number of
school
meals/snack
s provided
to Students
How much money
(KIP) did the school
spend in this month
to buy food from
farmers for
students?
Total Male Female Total Male Female New1 Continui
ng2
Male Female
# SCQ 801 SCQ 802 SCQ 803 SCQ 804 SCQ 805 SCQ 806 SCQ 807 SCQ 808 SCQ 809 SCQ 810 SCQ 811 SCQ 812 SCQ 813
1 September 2014
2 October 2014
3 November 2014
4 December 2014
5 January 2015
6 February 2015
7 March 2015
8 April 2015
9 May 2015
10 June 2015
11 July 2015
12 August 2015
13 September 2015
1 New students are those who have started receiving school meals/snacks from this month
2
Continuing students are those who have received food previously as well as continuing to receive in the current month
40
SCQ 900A What type of school meal did the school offer during the last academic year (2014-15)? 1. MMS; 2. MMS + THR; 3. Lunch
SCQ 900B What type of school meal did the school offer during the current academic year (2015-16)? 1. MMS; 2. MMS + THR; 3. Lunch
Section 9. Food Delivery Record
(Quantity of food received in the last 13 months)
SL Food delivery record (School level information)
(Put the amount in Kilogram (Kg) where amount is requested. Put zero “0” if no amount is received/lost this month or carryover from last month; Put 9999 if data is
not available; Put 99 if it’s not applicable))
August 2014 September 2014 October 2014 November 2014 December 2014 Amount Carryover stock from last month Amount of Food loss in this month Amount of Food received this month (skip to 907 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 912 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 917 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 922 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Amount of Food received this month (skip to 927 if amount is “0”)
Actual delivery date
Expected delivery date (planed)
# SCQ
901
SCQ
902
SCQ
903
SCQ
904
SCQ
905
SCQ
906
SCQ
907
SCQ
908
SCQ
909
SCQ
910
SCQ
911
SCQ
912
SCQ
913
SCQ
914
SCQ
915
SCQ
916
SCQ
917
SCQ
918
SCQ
919
SCQ
920
SCQ
921
SCQ
922
SCQ
923
SCQ
924
SCQ
925
SCQ
926
1
Rice –
(KG)
2
Flour
(CSB) –
(KG)
3
Oil–
(liter)
4
Sugar–
(KG)
5
Others–
(KG)
41
SL Food delivery record (School level information)
(Put the amount in Kilogram (Kg) where amount is requested. Put zero “0” if no amount is received/lost this month or carryover from last
month; Put 9999 if data is not available)
January 2015 February 2015 March 2015 April 2015 Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 932 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 937 if amount is “0l”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 942 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month
Amount of Food received this month
(skip to 947 if amount is “0”)
Actual delivery date
Expected delivery date (planed)
# SCQ 901
SCQ 927
SCQ 928
SCQ 929
SCQ 930
SCQ 931
SCQ 932
SCQ 933
SCQ 934
SCQ 935
SCQ 936
SCQ 937
SCQ 938
SCQ 939
SCQ 940
SCQ 941
SCQ 942
SCQ 943
SCQ 944
SCQ 945
SCQ 946
1 Rice – (KG)
2
Flour (Corn Soya Blend
/ CSB) – (KG)
3
Oil (vitamin A fortified)
– (Liter)
4
Sugar– (KG)
5
Others– (KG)
42
SL Food delivery record (School level information)
(Put the amount in Kilogram (Kg) where amount is requested. Put zero “0” if no amount is received/lost this month or carryover from last month; Put 9999 if data is
not available)
May 2015 June 2015 July 2015 August 2015 Sept 2015 Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 952 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 957 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 962 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month Food amount received (skip to 967 if amount is “0”) Actual delivery date Expected delivery date (planed) Amount Carryover stock from last month Amount of Food loss in this month
Food amount received
(END of Survey “0”)
Actual delivery date
Expected delivery date (planed)
# SCQ 901
SCQ 947
SCQ 948
SCQ 949
SCQ 950
SCQ 951
SCQ 952
SCQ 953
SCQ 954
SCQ 955
SCQ 956
SCQ 957
SCQ 958
SCQ 959
SCQ 960
SCQ 961
SCQ 962
SCQ 963
SCQ 964
SCQ 965
SCQ 966
SCQ 967
SCQ 968
SCQ 969
SCQ 970
SCQ 971
1
Rice –
(KG)
2
Flour
(CSB) –
(KG)
3
Oil–
(liter)
4
Sugar–
(KG)
5
Others–
(KG)
43
Parent/household Questionnaire
USDA McGovern Dole, Australian Aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Take Consent
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Section 1: Interview detail
# Question Response Code
HHQ 101 Province
HHQ 102 District
HHQ 103 School Name
HHQ 103_A School Code This code should be auto generated by the
tablet programme.
HHQ 104 Student Code (sample code) It is very important that enumerators do not put
wrong codes. Supervisors must check.
HHQ 105 Student name (sample student)
HHQ 106 Respondent Name
HHQ 107 Relationship of the respondent with the
student
1 = Father
2 = Mother
3 = Both
4 = other Family member / Legal guardian
HHQ 108 Household address (House Number, Unit)
HHQ 109 Household size (number of HH members)
HHQ 110 Number of pupils in pre-primary and
primary school within the HH
HHQ 111 Date of Interview
HHQ 112 Supervisor Code
HHQ 113 Supervisor Name
HHQ 114 Enumerator Code
HHQ 115 Enumerator Name
44
Section 2: Socio-Demographic Characteristics of All Household Members
I would like to ask you some questions about you and your household members. [Ask the name and then ask other questions about the head of household and repeat for all
other members]
QUESTIONS CODES
HHQ 203: Relationship- What is your / their relationship to the
household head?
1= head, 2 = spouse, 3 = child, 4 = grandchild, 5 = sibling, 6 = parent, 7 = parent-in-law, 8 = son/daughter-in-law,
9= Grandparent, 10=Uncle/aunty, 11 = other (specify)
HHQ 204: Sex - Are they male or female? 1= male, 2 = female
HHQ 205: Marital Status - What is your / their marital status? 1=unmarried, 2=married, 3=widow/er, 4=divorced/abandoned
HHQ 206: Education - What is the last school class the
household head / they passed?
0= no schooling, 1-12=last Grade passed, 13= higher diploma; 14= technical/ vocational diploma; 15= Bachelor or
equivalent, 16= Master or equivalent, 17=Pre-primary/Just enrolled, 18= Don’t know, 19=Other (and specify)
HHQ 207: Main Occupation - What is your / their main
occupation?
0 = Unemployed, 1=Paddy farmer, 2=Upland farmer, 3 =Cash crop farmers, (e.g. rubber, coffee, etc.), 4=Casual
labor (agricultural, industrial), 5=Hunting, 6=Fishing / Aquaculture, 7=Petty trade/business, 8=Official/employee
(public/private service), 9=Livestock / Poultry rearing, 10=Vegetable/crop garden, 11=Cottage industry/handicraft
/artisan, 12=Domestic maid, 13=Rickshaw/van/boat/push cart, 14=Transport worker (e.g. bus/truck), 15=Begging,
16=Rag picker/scavenging, 17=Housewife, 18=Student, 19 = Too old or too young to work, 21=Other (and specify)
HHQ 208: Average Monthly Income – What is his/her average monthly income either in cash or kind or both? (mention the amount in KIP)
SL Name Relationship Sex Marital Status Education Occupation Monthly Income
HHQ 201 HHQ 202 HHQ 203 HHQ 204 HHQ 205 HHQ 206 HHQ 207 HHQ 208
1 Start with Student
2 Then Household head 1
3
4
5
6
7
8
9
10
11
12
45
Section 3: Questions are related exclusively to the pupil through whom this HH member was selected
# Questions Response Code
HHQ
301 Which class/grade does (NAME of the CHILD) attend? Mention grade level / number
HHQ
302
Which part of the day does (NAME of the CHILD) spend in
the school?
1 = Morning
2 = Afternoon
3 = Whole day (both AM and PM)
HHQ
303
In the past 5 school days, how many days did (NAME of the
CHILD) eat breakfast at home? 0 to 5
HHQ
304
In the past 5 school days, how many days did (NAME of the
CHILD) eat lunch at home? 0 to 5
HHQ
305
In the past 5 school days, how many days did (NAME of the
CHILD) eat dinner at home? 0 to 5
HHQ
306
In the past 5 school days, how many days did you give
(NAME of the CHILD) a school tiffin/lunch/snacks?
(verify with other family members if parents can’t answer)
0 to 5
HHQ
307
In the past 5 school days, how many days did (NAME of the
CHILD) have mid-morning snacks / lunch at school?
(verify with other family members if parents can’t answer)
0 to 5
HHQ
308
On school days, when school meals are provided, do you
reduce the portion of food provided to the pupil compared to
the weekend?
1. Yes
2. No (skip to 310)
HHQ
309
If yes, on average how much do you reduce the portion
compared to the week end?
1. 1% - 25%
2. 26% -50%
3. 51% -75%
HHQ
310
In the past 5 school days, was there a time when the school
didn’t provide any food to (NAME of the CHILD)?
1. Yes
2. No
3. I don’t know
HHQ
311 If not, how did the child eat on those days?
1. Child brought own food and eats (or ate) at school
2. Gave cash to child to buy lunch
4. Child came home for lunch and then
went back to school
5. Child remained home and ate at home
6. No lunch / Skipped meal
7. Eat with friend/s
8. Other (Specify)
HHQ
312
During the past 30 days except the school holidays, did
(NAME of the CHILD) miss any school days?
1. Yes
2. No (skip to 318)
3. Don’t Know (skip to 318)
HHQ
313
What are the reasons for missing the school days?
(Multiple Response)
1 = Transportation issue
2 = child work on farm or livestock tending
3 = child looking after siblings or domestic work
4 = lack of food at home
5 = because of insecurity, fear of going to school
6 = sickness / illness
7 = ceremonies/festivals and family events
8 = School Punishment
9= No specific reason, the child just skipped the
school
10 = Other (specify)
HHQ
314
How many days did he/she miss due to lack of food at
home / hunger?
Number of days.
Put “00” if no days were missed due to this reason
HHQ
315 How many days did he/she miss due to illness? Number of days.
Put “00” if no days were missed due to this reason
HHQ
316
How many days did he/she miss from school to help family
with income generating activities?
Number of days.
Put “00” if no days were missed due to this reason
HHQ
317
How many days did he/she miss from school to help family
with household work in the field?
HHHQ
318 How many days did he/she miss for domestic work? Number of days.
Put “00” if no days were missed due to this reason
HHQ
319 Do you think, there is any benefit of primary education? 1. Yes
2. No (skip to HHQ 320)
46
HHQ
320
If Yes, can you mention some benefits of primary
education?
(Please do not tell the answers to the respondent, just record
his/her answers, if the respondent have given only one or two
answer, then probe whether he or she can think more benefits,
and try to list at least 3 benefit; however if they can’t mention,
move on to the next question)
(Multiple Response)
1. Improves literacy rate
2. Social Skill Development
3. Increases ability to learn new skills (adoption of
technology)
4. Girls remain more in school and early marriages
are delayed
5. Improves cohesion in the community
6. Helps break the cycle of poverty
7. Increases the chances of the pupils' future
economic self-reliance
8. Through girls' education, improves the general
wellbeing of households (nutrition, health etc.)
9. Other (specify)
HHQ
320A
Can you name a few behavior / practices that are important for
good health / hygiene
(Please do not tell the answers to the respondent, just record
his/her answers, if the respondent have given only one or two
answer, then probe whether he or she can think more benefits,
and try to list at least 3 benefit; however if they can’t mention,
move on to the next question)
(Multiple Response)
0. Can’t mention / Don’t know
1. Regular and proper use of latrine for at
community and school
2. Maintain and use sanitary latrine
3. Hand washing with soap after using latrine,
before eating / preparing food / feeding a child
4. Use and maintain tippy tap for hand washing
5. Drinking clean water from a safe source (e.g.
tube well, or treated water collected from river/lake)
6. Maintain a waste disposal system (Water
drainage, garbage pits, waste basket/dust bins)
7. Keep the School building and compounds clean
8. Maintaining hygienic environment during food
preparation, handling and distribution
9. Using clean and hygienic utensils during food
preparation, handling and distribution
10. Other (Specify)
HHQ
320B
Can you name a few local sources from where you can get
information good health practices?
(if the responded have given one answer and doesn’t give
more answer, do not need to push him/her for more
answer.)
(Multiple Response)
0. No response given
1. Local health clinic / hospital
2. School Health and hygiene Brochures
3. NGO/GoL Community health workers
4. Poster and Pamphlet
5. Notice board/ wall magazine / Wall
paintings/hording board
6. Radio / Television
7. Video/Documentary Street Drama Show
8. Newspaper / Magazine
9. Other (specify)
HHQ
321
Do you know about school feeding programme?
(Please explain to the parents what school feeding
programme means. They might not know the name school
feeding programme, but be aware that food is provided at
school)
1. Yes
2. No (skip to 322)
HHQ
322
If Yes, what are the benefits of school feeding program to
you and to the community/society
(Please do not tell the answers to the respondent, just record
his/her answers, if the respondent have given only one or two
answer, then probe whether he or she can think more benefits,
and try to list at least 3 benefit; however if they can’t mention,
move on to the next question)
(Multiple Response)
1. Improves school attendance
2. Promotes performance
3. Improves child nutrition levels
4. Reduces Hunger
5. Less expense on Food
6. Others (Specify)
HHQ
323
How can you get information about school feeding
programme or make complaints if necessary?
1. Don’t know
2. Regular meetings with VEDC
3. Regular meetings with School Administrators
4. Suggestion Box
5. Helpline
6. Informal communication (verbal) with teachers /
VEDC members
7. My child (student)
8. Other (specify)________
HHQ
324
Does the school have Parent Teacher Association or similar
governance structure?
1. Yes
2. No (skip to 325)
3. Don’t Know (skip to 325)
HHQ
325 If Yes, are you part of any Parent Teacher Association? 1. Yes
2. No
HHQ
326
Are you aware of the existence of the Village Education
Development Committee (VEDC)?
1. Yes
2. No (skip to HHQ 327)
47
HHQ
327
If Yes, what is your perception of the Village Education
Development Committee (VEDC) involvement in the SFP?
1= High
2= Medium
3= Low
HHQ
328
In the past 30 days, were there any cases of physical
and/or emotional threats to the safety of your child that
he/she was exposed to when going to and coming back
from school or at school?
1. Yes
2. No (skip to Section 4)
3. Don’t Know (skip to Section 4)
HHQ
329
If Yes, please indicate the type of threats:
(Multiple Response)
1. Rape
2. Sexual Harassment
3. Robbed
4. Animal Attacks
5. Bullying / Teasing
6. Abuse of drugs
7. Punishment at school
8. Others (specify)
Section 4: Dietary Diversity
(Questions are related exclusively about the pupil through which this HH member was selected)
SL
Food Items
(In the last 24 hours (during the day and night), did (CHILD NAME) eat any of these food items? Ask
about every single items and record the answer. If any items are consumed less than one tea
spoon, record response “2. NO”; Only count them “1.YES” if consumed ≥1 teaspoon.)
1=Yes
2=No
9 = Don’t know
STQ
401 STQ 402 STQ 403
1 Food made from grains, such as bread, rice, noodles, porridge, or [other local grain food]
2
White potatoes, white yams, manioc, cassava, [other local root crops] or any other foods made from
roots
3 Any foods made from beans, peas, or lentils, such as [add any local legume names]
4 Any foods made from nuts or seeds such as [add any local nut/seed names]
5 Milk
6 Cheese, yogurt, or other milk products
7 Eggs
8
Any liver, kidney, heart, or other organ meats from domesticated animals, such as cattle, swine,
goat, chicken, or duck
9
Any liver, kidney, heart, or other organ meats from wild animals, such as [names of local commonly￾consumed wildlife]
10 Any meat, such as beef, pork, lamb, goat, chicken, or duck
11 Any flesh from wild animals, such as [names of local commonly-consumed wildlife]
12 Fresh or dried fish, shellfish, or seafood, shrimps, crabs
13 Grubs, snails, frogs or insects such as worms Grasshoppers, larvae, [add any local insect names]
14 Any dark green leafy vegetables such as [local dark green leafy vegetables] Bamboo shoots,
pumpkin shoots, long bean
15 Pumpkin, carrots, squash, or sweet potatoes that are yellow or orange inside or [other local
yellow/orange foods]
16 Ripe mangoes, ripe papayas or [other local vitamin A-rich fruits] guava
17 Foods made with red palm oil, red palm nut, or red palm nut pulp sauce (Vitamin A rich oil)
18 Any other vegetables
19 Any other fruits
Additional food items
20 Any oil, fats, or butter, ghee, or foods made with any of these
21 Sweets: sugar, honey, sweetened soda or sweetened juice drinks, sugary foods such as
chocolates, candies, cookies and cakes
22 Condiments for flavor, such as chilies, spices, herbs, fish powder or [add any local condiment
names]
48
Student Questionnaire
USDA McGovern Dole, Australian aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Take Consent
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Interview detail
# Question Response Code / instructions
STQ 101 Province
STQ 102 District
STQ 103 School Name
STQ103_A School Code
STQ 104 Student Code Be careful to put the right number.
STQ 105 Student name
STQ 106 Sex 1=Male
2=Female
STQ 107 Age (months) Probe and get the correct age.
STQ 108 Current Grade/Class
STQ 109 Father' name
STQ 110 Mother's name
STQ 111 Date of Interview _____/_____/_____ Day/Month/Year (e.g. 15 / 04 / 2012)
STQ 112 Supervisor Code
STQ 113 Supervisor Name
STQ 114 Enumerator Code
STQ 115 Enumerator Name
49
Section 2
These questions are applicable for regular school days. If the child didn’t go to school before the interview date, ask about
last school day.
Ask about
last 24 hours
Did you
have a meal
/snack?
(1. Yes; 2.
No)
If no, Skip to
STQ_206
Was this meal
enough for
you?
(1. Yes; 2. No)
(ask the
student if s/he
was still
hungry after
the meal)
What was the
timing in
relation to the
school hours?
1. Before school
2. During school
hours (8 am – 4
pm)
3. After school
If during school hours,
where did this meal come
from?
1. Meal provided by school
2. Bring own food and eat at
school
3. Pay for lunch e.g. kiosk or
school canteen
4. Went home for lunch and
then came back
5. Other (specify)
If didn’t have this
meal, what was the
main reason?
1. this is not part of
regular consumption
practice
2. not hungry
3. Didn’t have food
4. illness
5. not enough time
6. Other (specify)
STQ 201 STQ 202 STQ 203 STQ 204 STQ 205 STQ 206
Early morning
(Breakfast
time)
Mid -
morning
Mid-day
(lunch time)
Mid –
afternoon
Evening
(dinner time)
Question Response Code
STQ
207
In the past 5 school days, how many days did you eat
breakfast before going to school?
0 to 5
STQ
208
In the past 5 school days, how many days did you eat
a meal after going to school (and before going to
bed)?
0 to 5
STQ
209
How long does it take to
get to school?
Number of minutes
STQ
210
How do you travel to school? 1= walking
2=by bicycle,
3=by car,
4=by bus,
5=by motorbike,
6 = other local transport (put rickshaw / Van /
other local option)
7=other
STQ
211
How many days per week do you take extra lessons
after school?
Put the number of days.
Put “0” if doesn’t take extra lessons
STQ
212
How many days per week do you work at home
before going to school?
Put the number of days.
Put “0” if doesn’t work
STQ
213
How many days per week do you work at home after
coming home from school?
Put the number of days.
Put “0” if doesn’t work
STQ
214
Does the meal (lunch/snack) provided act as an
incentive for going to school every day?
1=Yes
2=No
STQ
215
If no meal is provided do you return home before the
end of the school day?
1=Yes
2=No
3 = Don’t know / not sure / didn’t happen
STQ
216
Normally, if you become aware that the school food
is finished, do you go to school the next day?
1=Yes
2=No
3 = Not sure / Don’t know
STQ
217
In the last 30 days how many school days have you
missed due to illness?
Put the number of days.
Put “0” if didn’t miss a day
50
STQ
218
Can you name a few behavior / practices that are
important for good health / hygiene
(Please do not tell the answers to the respondent, just
record his/her answers, if the respondent have given
only one or two answer, then probe whether he or
she can think more benefits, and try to list at least 3
benefit; however if they can’t mention, move on to
the next question)
(Multiple Response)
0. Can’t mention / Don’t know
1. Regular and proper use of latrine for at
community and school
2. Maintain and use sanitary latrine
3. Hand washing with soap after using latrine,
before eating / preparing food / feeding a child
4. Use and maintain tippy tap for hand
washing
5. Drinking clean water from a safe source
(e.g. tube well, or treated water collected from
river/lake)
6. Maintain a waste disposal system (Water
drainage, garbage pits, waste basket/dust
bins)
7. Keep the School building and compounds
clean
8. Maintaining hygienic environment during
food preparation, handling and distribution
9. Using clean and hygienic utensils during
food preparation, handling and distribution
10. Other (Specify)
STQ
219
Can you name a few local sources from where
you can get information good health practices?
(if the responded have given one answer and
doesn’t give more answer, do not need to push
him/her for more answer.)
(Multiple Response)
0. No response given
1. Local health clinic / hospital
2. School Health and hygiene Brochures
3. NGO/GoL Community health workers
4. Poster and Pamphlet
5. Notice board/ wall magazine / Wall
paintings/hording board
6. Radio / Television
7. Video/Documentary Street Drama Show
8. Newspaper / Magazine
9. Other (specify)
51
EGRA Questionnaire
USDA McGovern Dole, Australian aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Take Consent
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Interview detail
# Question Response Code
STQ 101 Province
STQ 102 District
STQ 103 School Name
STQ103_A School Code
STQ 104 Student Code Be careful with student codes
STQ 105 Student name
STQ 106 Sex 1=Male
2=Female
STQ 107 Age (months) (If necessary verify the age with teachers)
STQ 108 Current Grade/Class Only grade 3
STQ 109 Father' name
STQ 110 Mother's name
STQ 111 Date of Interview _____/_____/_____ Day/Month/Year (e.g. 15 / 04 / 2012)
STQ 112 Supervisor Code
STQ 113 Supervisor Name
STQ 114 Enumerator Code
STQ 115 Enumerator Name
Section 2
Question Response Code
STQ 201 How long does it take for you to get to
school?
Number of minutes
STQ 202 Do you have anyone at home (family
members / relatives / neighbors but not
private teachers) to help you with reading?
1. Yes
2. No
3. Don’t know
STQ 203 What is the level of your father’s
education?
0= no schooling, 1-12=last Grade passed,
13= Bachelor or equivalent, 14= higher
diploma; 15 = technical/ vocational
diploma; 16= Master or equivalent,
17=Pre-primary/Just enrolled, 18= Don’t
know, 19=Other (and specify)
STQ 204 What is the level of you Mother’s
education?
STQ 205 Do you read any extracurricular book? 1. Yes
2. No (Skip to 207)
STQ 206 If yes, did you read any story within last 7
days?
Number
52
STQ 207 How many days per week do you take
extra lessons after school?
Put the number of days.
Put “0” if doesn’t take extra lessons
STQ 208 How many days per week do you work at
home before going to school?
Put the number of days.
Put “0” if doesn’t work
STQ 209 How many days per week do you work at
home after coming home from school?
Put the number of days.
Put “0” if doesn’t work
STQ 210 What kind of roof does your house have? 1. Grass/leaves / straw
2. Plastic / polyethylene
3. Bamboo
4. Wood
5. Tile
6. Metal (Iron / Tin)
7. Don’t know
8. Others, please specify
STQ 211 What kind of walls does your house have? 1. Mud / clay
2. Grass / leaves / Straw
3. Bamboo
4. Wood
5. Brick & Cement
6. Metal (Iron / Tin)
7. Brick & wood (brick for ground floor and
wooden first floor)
7. Don’t know
8. Others, please specify
STQ 212 Does your home have any of these items?
(circle all that apply)
1. Radio
2. Electricity
3. Refrigerator
4. Bicycle
5. Latrine
6. Mobile phone
7. Television
8. Motorbike
9. Car
10. Tractor (tok tok)
11. None of the above items
STQ 213 What type of water do you usually drink at
home?
(circle all that apply)
1. Well
2. Pumped / tube well
3. Piped water
4. Pond
5. River
6. Stream
7. Treated water from factory (can be in
the bottle, plastic container)
8. Rain water
9. Spring water
10. Tap water from gravity-fed water
system (Nam Lin)
11. Other (specify)
STQ 214 In past 30 days (in a week) how many
times did you get sick?
Put number of time s/he got sick
If “00” move to SCQ 216
STQ 215 In past 30 days (in a week) how many
days did you skipped school due to
illness?
STQ 216 In past 7 days, how many days did you
come to school?
0 - 5 days
If “00” move to SCQ 301
STQ 217 In the past 7 days, how many days were
you at school full day (morning and
afternoons) last week?
0 - 5 days
STQ 218 How many days did you receive meal from
school?
0-5 days
(response ≤ SCQ216)
53
Section 3: Student Reading & Understanding skills
(Applicable only for students at the end of grade 2 / beginning of grade 3)
# Questions Response Code / hints
STQ 301 Which ethnic group do you belong to? 1. Hmong – Eiw Mien
2. Mon - Khmer
3. Lao - Tai
4. Chinese - Tibetan
5. Other (Specify)
STQ 302 What language do you speak at home? 1. Hmong – Eiw Mien
2. Mon - Khmer
3. Lao - Tai
4. Chinese - Tibetan
5. Other (Specify)
Achievement in different section of the test
Letter Recognition
(The full set of letters of the alphabet is listed in random order, 5 letters to a row, using a clear, large, and familiar font)
STQ 303 Letters read in first 60 seconds (skip to STQ 307 if response is “00”)
STQ 304 Number of incorrect letters in first 60 seconds
(if the words are skipped then they will also
be counted as mistake)
Number of mistakes
At the end of 1 minute, circle the letter the child is reading and allow the student to finish the letters if he/she is reading.
Continue marking which letters are read incorrectly with a slash ( / ).
STQ 305 Total letters read Number
STQ 306 Total number of incorrect letters
(if the words are skipped then they will also
be counted as mistake)
Number of mistakes
Familiar Word Recognition
(20 simple selected words, 5 words to a row, using a clear, large, and familiar font)
STQ 307 Familiar Words read in 60 seconds Number of words
(skip to STQ 311 if response is “00”)
STQ 308 Total incorrect words in 60 seconds
(if the words are skipped then they will also
be counted as mistake)
Number of mistakes
At the end of 1 minute, circle the word the child is reading and allow the student to finish the passage. Continue marking
which words are read incorrectly with a slash ( / ).
STQ 309 Total familiar Words read Number of words
STQ 310 Total incorrect words
(if the words are skipped then they will also
be counted as incorrect words)
Number of mistakes
Decoding Words (Invented word reading)
(20 invented words, 5 words to a row, using a clear, large, and familiar font)
STQ 311 Non-sense Words read in 60 seconds Number of words
(skip to STQ 315 if response is “00”)
STQ 312 Total incorrect Non-sense words in 60
seconds
(if the words are skipped then they will also
be counted as incorrect words)
Number of mistakes
54
At the end of 1 minute, circle the word the child is reading and allow the student to finish the passage. Continue marking
which words are read incorrectly with a slash ( / ).
STQ 313 Total Non-sense Words read
STQ 314 Total incorrect Non-sense words
(if the words are skipped then they will also
be counted as incorrect words)
Number of mistakes
Fluency and Accuracy
STQ 315 Total Words read in 60 Second from the
paragraph
Number of words
(skip to STQ 320 if response is “00”)
STQ 316 Total incorrect words in 60 seconds
(if the words are skipped then they will also
be counted as incorrect words)
Number of incorrect words
At the end of 1 minute, circle the word the child is reading and allow the student to finish the passage. Continue marking
which words are read incorrectly with a slash ( / ).
STQ 317 Total words read from the paragraph
STQ 318 Total incorrect words
Reading Comprehension
STQ 319 Total number of correct answers given
Listening Comprehension
STQ 320 Total number of correct answers given
55
Teacher Questionnaire
USDA McGovern Dole, Australian Aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Take Consent
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Interview detail
# Question Response Code
TEQ 101 Province
TEQ 102 District
TEQ 103 School Name
TEQ 104 School Code
TEQ 105 Teacher Code Carefully put teacher’s code and don’t make mistake
TEQ 106 Date of Interview ____/____/____ Day/Month/Year (e.g. 15 / 04 / 2015)
TEQ 107 Supervisor Code
TEQ 108 Supervisor Name
TEQ 109 Enumerator Code
TEQ 110 Enumerator Name
Section 2: Teacher Activities and Classroom Environment
# Question Response Code Comments from
pre-test
TEQ 201 What is your name?
TEQ 202 Sex of the teacher 1. Male
2. Female
TEQ 203 For how many years have
you been teaching?
Number of years
TEQ 204 How many years have you
been teaching at this
school?
Number of years
TEQ 205 What position do you hold
at this school?
1. Head teacher/ principal
2. Deputy head teacher
3. Teacher (permanent/ regular)
4. Teacher (paid contract)
5. Teacher (volunteer)
6. Other (specify)
56
TEQ 206 What is your highest
education qualification?
1. MSc or higher
2. Bachelor
3. Diploma
3. Higher/Advanced diploma (San Soung)
4. Technical/vocational Diploma (San Kang)
5. Higher Secondary
6. Secondary
7. Primary
8. Untrained
9. Other
TEQ 207 Which grade do you
teach?
(Multiple Response)
1. Grade 1
2. Grade 2
3. Grade 3
4. Grade 4
5. Grade 5
6. Pre-primary
TEQ 208 What subject do you teach
at school?
(Multiple Response)
1. Literature / Language ( Lao)
2. Literature / Language (English / other
foreign language)
3. Science
4. Mathematics
5. Social science/World around us (Loke om
tua)
6. Religion
7. History
8. Arts / Painting
9. Life skills
10. Others
TEQ 209 Do you have any formal
training on teaching from
government / non￾government institutes?
1. Yes
2. No
TEQ 210 In the last 30 days, how
many days did you spend
for teaching at school?
Number of days
Put “00” if none
TEQ 211 In the last 30 days how
many times were you
absent from school?
For enumerators:
[Check in
conjunction with
210]
TEQ 212 Do you tutor students
outside school hours?
1=yes, with pay
2=yes, without pay
3 = Both
4= Don’t tutor
TEQ 213 In the last 30 days, how
many days did you spend
for private tutoring
outside school?
Number of days
Put “00” if none
TEQ 214 Do you have another job /
work outside the school
other than tutoring?
1=Yes
2=No
TEQ 215 What proportion of
students in your
classroom has the
required textbook/s for
the class?
1=None,
2=1-25%
3=26-50 %
4=51-75 %
5=76-99%
6 = 100 %
7 = Don’t know
57
TEQ 216 What proportion of
students in your
classroom has a desk and
chair?
1=None,
2=1-25%
3=26-50 %
4=51-75 %
5=76-99%
6 = 100 %
7 = Don’t know
TEQ 217 Do you think the provision
of school meals
significantly impacts the
decision of children to
come to school?
1. Yes
2. No
3. Don’t Know
TEQ 218 According to you, if WFP
SFP would stop today,
what would be the
consequence on pupil
attendance?
1. No consequence, attendance will remain
the same
2. Attendance will drop slightly (10%)
3. Attendance will drop significantly (10%-
30%)
4. Attendance will drop drastically (over
30%)
TEQ 219 According to you, if WFP
SFP would stop today,
what would be the
consequence on pupil
Enrollment?
1. No consequence, Enrollment will remain
the same
2. Enrollment will drop slightly (10%)
3. Enrollment will drop significantly (10%-
30%)
4. Enrollment will drop drastically (over
30%)
TEQ 220 In your observation, what
percent of students in
classrooms can be
identified as inattentive?
TEQ 221 What do you do to engage
students and parents to
improve the learning
outcome?
(Multiple response)
1. Rewarding certificates to students to
take to home
2. Sending letters to parents explaining
about children's reading performance
3. Join special tutoring class
4. Doing nothing
Section 3: Teacher Compensation & Income
# Question Response Code
TEQ 301 What is your monthly income from school? Income in KIP (salary + benefits)
TEQ 302 How much do you earn monthly from tutoring
outside school hours?
Income in KIP
TEQ 303 How much do you earn monthly from other
sources?
Income in KIP
TEQ 304 Do you think your salary is sufficient to cover
your living expenses?
1=Yes
2=No
TEQ 305 Do you get your salary on time every month? 1=Yes
2=No
TEQ 306 If there is a delay in getting monthly salary,
how long does it usually take?
Number of days
58
Storekeeper Questionnaire
USDA McGovern Dole, Australian Aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Take Consent
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Interview detail
# Question Response Code
SKQ 101 District
SKQ 102 School Name
SKQ 103 Respondent name
SKQ 104 Sex of the Respondent:
___
1. Male
2. Female
SKQ 105 Date of Interview ____/____/____ Day/Month/Year (e.g. 15 / 04 / 2015)
SKQ 106 Supervisor Code
SKQ 107 Supervisor Name
SKQ 108 Enumerator Code
SKQ 109 Enumerator Name
Section 2: School feeding program information
# Question Response Code
STQ 201 Does your school have a dedicated food store room? 1. Yes
2. No
STQ 202 Is the food store room lockable?
ASK QUESTION +OBSERVATION
1. Yes
2. No
STQ 203 Is the store room properly ventilated?
DIRECT OBSERVATION
1. Yes
2. No
STQ 204 Is there any evidence of presence of rodents in the store?
ASK QUESTION +OBSERVATION
1. Yes
2. No
STQ 205 Is there any evidence of presence of insects (weevil and others)?
ASK QUESTION +OBSERVATION
1. Yes
2. No
STQ 206 Is there any evidence of mold and excess of humidity?
ASK QUESTION +OBSERVATION
1. Yes
2. No
STQ 207 Is there any evidence of spillage or leakage?
ASK QUESTION +OBSERVATION
1. Yes
2. No
STQ 208 Is the food stored off the ground?
ASK QUESTION +OBSERVATION
1. Yes
2. No (go to Q210)
59
STQ 209 If yes, does the school use improvised raised pallets for commodities'
storage?
ASK QUESTION +OBSERVATION
1. Yes
2. No
STQ 210 Does the school have a pest/insects management plan? 1. Yes
2. No
STQ 211 Does the school carry out pest/insects control measures? 1. Yes
2. No
STQ 212 Are you trained in safe food preparation and storage practices? 1. Yes
2. No (Skip to 214)
STQ 213 If Yes, how many times have you received training in last one year?
STQ 214 Have you received a book about Warehouse management in Lao
language within the last 12 months
1. Yes
2. No
STQ 215 Do you maintain proper record of the food items?
(Ask Question + Observation)
1. Yes
2. No
STQ 216 Have you received your incentive ration for being a storehouse
manager
1. Yes
2. No (End of
interview)
STQ 217 Do you consider your ration as enough 1. Yes
2. No
STQ 218 What did you do with your ration 1. Consumed it
2. Exchanged it for
other foods/
goods (bartering)
3. Sold it at the
market
4. Gave it away (
gift)
60
Cook Questionnaire
USDA McGovern Dole, Australian Aid and WFP supported Food for
Education Programme in Lao PDR: Baseline Survey 2015
Take Consent
Did the respondent give consent to take part in this survey? 1. Yes
2. No (End of Survey)
Interview detail
# Question Response Code
Q 101 District
Q 102 VDC
Q 103 School Name
Q 104 Respondent name
Q 105 Sex of the Respondent:
___
1. Male
2. Female
Q 106 Date of Interview ____/____/____ Day/Month/Year (e.g. 15 / 04 / 2015)
Q 107 Supervisor Code
Q 108 Supervisor Name
Q 109 Enumerator Code
Q 110 Enumerator Name
Section 2: School feeding program information
# Question Response Code
Q201 Are you trained in safe food preparation and storage practices
(confirm with any records, if available)?
1. Yes
2. No (go to Q203)
Q202 If Yes, how many times have you received training in 2014? __________
Q203 Have you received a cookbook? 1. Yes
2. No
Q204 Do children wash their hands before the meal? 1. Yes
2. No
Q205 Have you received a food ration to cook for the children in schools? 1. Yes
2. No
Q206 What did you receive as an incentive ration? 1. Rice
2. Flour
3. Cash
4. Nothing
Q207 How much food did you receive as an incentive ration in last month? Put the amount in
KG
Q208 Do you use smoke reducing stoves? 1. Yes
2. No
Q209 Have you received any training in using smoke reducing stoves 1. Yes
2. No
Q210 Have you received smoke reducing stoves 1. Yes
2. No
61
Q211 Are the cooks clean and well groomed?
DIRECT OBSERVATION
1. Yes
2. No
Section 3: Safe Food Preparation Practices (for Cook)
# Question Response Code
Q301 Do you have a uniform or apron for
use in the kitchen?
1. Yes
2. No
Q302 When do you clean your kitchen? 1. Every morning before food preparation, often during the
day and after use
2. After food preparation
3. At the end of the week
4. Other (specify)
Q303 Which is the best source of water
for cleaning and cooking food?
1. Piped water, rain water and boreholes which are well
protected
2. Water from the river/streams
3. Water from a pond
4. Bottled water
5. Other
Q304 When do you usually wash your
hands for food preparation?
1. Before handling food and often during food preparation
2. After using the latrine
3. After finishing food preparation
4. Never (Skip to 306)
5. Other (specify)
Q305 How do you wash your hand? 1. Only with Water
2. Water with Soap
3. Water with Mud
4. Water with Ash
5. Other (Specify)
Q306 How do you ensure that food is
clean before cooking?
1. Rinse it in water and cook
2. Remove foreign matters then cook
3. Use clean containers to collect it from the store, remove
foreign matters and then wash it with clean water
thoroughly before cooking
Q307 When do you wash your cooking
utensils (cooking pots, lids, scoops,
knives, plates etc.) with clean
water and soap
1. After use
2. Prior to using them
3. Prior to, after using them and drying them in a rack before
storage
Q308 Are there measures in place to
prevent food from contamination
from pests and rodents? Name
them:
1. ____________________________
2. ____________________________
Q309 What is the most important thing
to check in food before cooking?
1. Expiry date, packaging, color of the food, presence of
pests
2. Source of food
3. Colour of the package
Q310 How do you store cooked food
prior to serving the pupils?
1. Store cooked food in covered cooking pots in a clean, safe
place before serving the pupils
2. Store cooked food in open containers
3. Store cooked food outside the kitchen without covers
62
Annex 3: Baseline Values of Key Indicators, with Calculations
Table 5: WFP Laos SFP performance indicators and their calculation by sex, geographical location and intervention type
Result
level Indicator Source and measurement
Effectiv
e
sample
size
Avg.
value
Value by sex
Value by
geographical
location
Value by
intervention
type
Male Female North South MMS Lunch
MDG
SO1
Percent of students who,
by the end of two grades
of primary schooling,
demonstrate that they
can read and understand
the meaning of grade￾level text
Pupils reading and understanding ability was
assessed using the literacy boost questionnaire
developed by Save the Children Laos.
Questionnaire was administered to 830 students
from Grade 3. The assessment had five sub-tests
and students were categorised into emergent,
beginner and reader with comprehension ability
based on comprehension sub-test score, as
recommended in Literacy Boost guideline. Students
demonstrating >75% comprehension are given here.
830 1.9 3 1.7 2.2 2.5 1.1 2.9 0.8
MGD
1.1.1
Average teacher
attendance rate (Mean ±
SE)
Teacher attendance was assessed using monthly
school records of every teacher’s attendance and
comparing this data against the number of school
days per month in the academic year September
2014-August 2015.
321 94
(±0.4)2
94
(±0.5)
94
(±0.6)
95
(±1.0)
92
(±0.8)
94
(±0.9)
93
(±0.9)
Percent of teachers
attending at least 90
percent of the school
days
Regular teacher attendance was defined as
attending more than or equal to 90 percent of school
days; teacher attendance was assessed using
monthly school records of all the teacher from
sample schools and the number of working days per
month for the academic year September 2014-
August 2015.
321 84 2 83 85 92 74 87 80
MGD
1.1.4
Percent of teachers/
educators/ teaching
assistants trained or
575 23 ns 20 26 26 19 26 20
63
Result
level Indicator Source and measurement
Effectiv
e
sample
size
Avg.
value
Value by sex
Value by
geographical
location
Value by
intervention
type
Male Female North South MMS Lunch
certified in teaching
techniques during the last
one year
Percent of teachers/
educators/ teaching
assistants in target
schools who demonstrate
use of new and quality
teaching techniques or
tools as identified by their
supervisor/mentor/coach
Teachers, educators, teaching assistants who have
successfully completed a pre- or in-services training
programme to teach in schools or equivalent non￾school based settings over the past one year were
then assess whether they are using the learned
techniques. Use of techniques were assess by
asking their supervisors whether the teacher is using
the techniques he/she learned in the classroom.
134 100 - - - - - -
MGD
1.2
Percent of students in
classrooms identified as
inattentive by their
teachers
Inattentiveness of students was collected based on
the majority view of three teachers on the
attentiveness of ten sampled students from each
school
850 19 1,3 22 16 19 19 13 26
MGD
1.3
Average student
attendance (Mean ± SE)
Student attendance was assessed using monthly
school records of ten sample students from every
school and comparing this data against the number
of school days per month in the academic year
September 2014-August 2015.
367 97
(±0.2)2
97
(±0.3)
97
(±0.3) 99 94 98
(±0.2)
96
(±0.4)
Percent of students
regularly (at least 80
percent of the school
days) attending school
Student attendance was measured using the
attendance record of ten randomly selected students
from every sample school for the last academic year
(September 2014-August 2015).
367 99.5 ns 99.5 99.4 100 99 99.5 99.3
Student attendance on
the day of the survey
The proportion of enrolled students present at
school during the survey day was calculated using
direct observation to count the number of students
present and comparing it against the number of
85 89 (±1.4)
2
88
(±1.4)
89
(±1.4)
94
(±1.1)
81
(±2.4)
90
(±2.2)
87
(±1.6)
64
Result
level Indicator Source and measurement
Effectiv
e
sample
size
Avg.
value
Value by sex
Value by
geographical
location
Value by
intervention
type
Male Female North South MMS Lunch
enrolled students. The mean proportion of students
in attendance is presented here.
MGD
1.3.4
Annual percent change in
students enrolled in WFP
supported school
Enrolment figures from the past five academic years
were collected from school records –where
available; student numbers of each academic year
were then compared with the previous academic
year. Percent change of enrolment in the current
academic year (2015-16) compared to the last
academic year (2014-15) is presented here.
79 -0.7 nt
-0.4 -1.0 -1.5 0.9 0.2 -1.8
Average enrolment ratio
of girls to boys at target
schools
Total number of male and female students per
school was recorded for past five academic year
from the school records during the baseline survey.
Ratio was calculated based on enrolment figures for
the past academic years. Girl-boy enrolment ratio for
last academic year (2014-15) is presented here.
79 0.95 nt
- - 0.95 0.95 0.93 0.98
Average dropout rate
(Mean± SE of percent)
Dropout figures from the past academic years were
collected from school records –where available.
Dropout rate was calculated per school from number
of students discontinuing their studies and enrolment
figures for the same academic year. Dropout rate for
last academic year (2014-15) is presented here.
66 0.8
(±0.2) 2,3
1.2
(±0.4)
0.5
(±0.2)
0.18
(±0.1)
1.86
(±0.6)
0.1
(±0.1)
1.4
(±0.4)
Repetition rate (Mean±
SE of percent)
Total number of male and female students repeating
in the same grade per school was recorded the
baseline survey data collection. Repetition rate was
calculated per school from number of repeating
students and enrolment figures for the same
academic year. Repetition rate for last academic
68 7.8
(±0.8) 1
9.5
(±1.2)
6.0
(±0.6)
7.3
(±1.1)
8.4
(±1.2)
9.1
(±1.3)
6.7
(±1.0)
65
Result
level Indicator Source and measurement
Effectiv
e
sample
size
Avg.
value
Value by sex
Value by
geographical
location
Value by
intervention
type
Male Female North South MMS Lunch
year (2014-15) is presented here.
MGD
1.3.5
Percent of parents in
programme schools who
can name at least three
benefits of primary
education
Data was collected through interviews with parents
and asking them about the benefits of primary
education. 810 45 2,3 48 43 42 50 38 53
MGD
SO2
Average dietary diversity
score (DDS) of school￾aged children (Mean ±
SE)
Dietary history of pupils was measured through
interviewing parents using a 24 hours recall method.
Mean Dietary Diversity Score (±SE) is presented
here.
810 5.0
(±0.06)2,3
5.0
(±0.09)
5.0
(±0.09)
5.2
(±0.09)
4.8
(±0.08)
5.3
(±0.09)
4.7
(±0.08)
MGD
2.1
Percent of students in
target school who
achieve a passing score
on a test of good health
and hygiene practices as
a result of USDA
assistance
The good health and hygiene practices were
identified in collaboration with WFP during the
questionnaire development phase and included into
the questionnaire to test the baseline knowledge of
students enrolled in WFP supported schools.
Students in target schools receiving at least a score
of 80 percent on the test of good health and hygiene
practices were considered as passed.
850 0.0 - - - -
MGD
2.2
Percentage of food
preparers at target
schools who achieve a
passing score (80
percent correct answer)
in a test of safe food
preparation and storage
practices
Percentage was calculated by testing cooks on safe
food preparation and storage. The test contained ten
questions, each worth one point. Respondents were
asked to choose the best response for each
question. The questions were developed in
collaboration with the country office, to assess the
baseline knowledge level and practices of food
prepares on safe food preparation and storage
practices.
85 8.2 ns
- - 8.0 8.6 8.9 7.5
ns = No significant difference between gender (sex), geographical location or intervention types. 1 = Only significant difference between boys and girls. 2 Only significant difference between north and south. 3 Only
significant difference between intervention types
Table 6: Key school variables by geographical location (north or south) and intervention type
Indicator Source and measurement
Baseline
questionnaire
name
Question￾naire ID
Effective
sample
size
Average
value
Values by
geographical
location
Values by
intervention type
North South MMS Lunch
Student teacher ratio in
target schools
Number of students currently enrolled
and number of teachers appointed in
the school were counted using school
records. Student:teacher ratio is
presented here.
School
Questionnaire
SCQ 301;
SCQ 401
85 27 (±1.3)1
21.6
(±1.2)
34.5
(±2.1) 26 (±1.6) 27 (±2.1)
Student classroom ratio
in target schools
Number of students currently enrolled
and number of classrooms available
in the school were counted using
school records and direct observation.
Student:classroom ratio is presented
here.
School
Questionnaire
SCQ 301;
SCQ 502-
503 85 28 (±1.2)1
25.0
(±1.5)
32.6
(±1.6) 28 (±1.6) 28 (±1.7)
Percent of school with
library facilities
The availability of library room or
library corner at school was identified
through head teacher interview and
direct observation.
School
Questionnaire
SCQ 302
85 74 1 58 97 71 78
Percent of schools with
dedicated storage rooms
Interview of the storekeeper and
verification by direct observation.
Storekeeper
questionnaire
SKQ 201 85 97.5 ns 96 100 95.6 100
Percent of store rooms
rehabilitated / constructed
as a result of USDA
assistance
Interview of the head teacher. School
Questionnaire
SCQ 315
85 25 1,2 8.0 49 11 40
Percent of schools where
food is stored off the
ground
Interview of the storekeeper and
verification by direct observation.
Storekeeper
questionnaire
SKQ 208
85 80 1 98 54 73 88
67
Indicator Source and measurement
Baseline
questionnaire
name
Question￾naire ID
Effective
sample
size
Average
value
Values by
geographical
location
Values by
intervention type
North South MMS Lunch
Percent of school with a
kitchen
Interview of the head teacher and
direct observation.
School
Questionnaire
SCQ 308 85 92 ns 94. 89 91 93
Percent of schools using
smoke reducing/Energy
saving stoves
Interview of the head teacher. School
Questionnaire
SCQ 310
85 0.0 - - - -
Percent of schools
received Smoke
reducing/ Energy Saving
Stove from WFP/USDA in
last one year
Interview of Cook Cook
Questionnaire
SKQ 210
85 0.0 - - - -
Percent of schools with a
dining area for the school
meals
Interview of the head teacher. School
Questionnaire
SCQ 311
85 9.4 1,2 2.0 20 2.2 18
Percent of storekeepers
trained in safe food
preparation and storage
practices as a result of
USDA assistance
Storekeeper interview Storekeeper
Questionnaire
SKQ 212-
213
85 45 1,2 26 60 22 70
Percent of storekeepers
received a book about
Warehouse management
in Lao language within
the last 12 months
Storekeeper interview Storekeeper
Questionnaire
SKQ 214
85 55 1 46 69 56 55
Percent of cook / food
preparers trained in safe
food preparation and
storage practices as a
result of USDA
Interview of one food preparer / cook
per school.
Cook
Questionnaire
SKQ 201-
202
85 33 1,2 24 46 22 45
68
Indicator Source and measurement
Baseline
questionnaire
name
Question￾naire ID
Effective
sample
size
Average
value
Values by
geographical
location
Values by
intervention type
North South MMS Lunch
assistancece
Percent of schools with a
source of drinking area
near or at school
Interview of the head teacher and
also direct observation
School
questionnaire
SCQ 312
85 44 ns 42 46 42 45
Percent of schools with
toilet facility for students
Interview of the head teacher and
also direct observation
School
questionnaire
SCQ 317 85 85 ns 90 77 84 85
Percent of schools with
separate toilet for female
students
Interview of the head teacher and
also direct observation
School
questionnaire
SCQ 319
85 25 1 16 41 26 24
Average distance (km) to
nearest food market
Interview of the head teacher School
questionnaire
SCQ 210 85 17
(±1.7)1,2 20 (±2.6) 12 (±1.7) 19 (±2.9) 13 (±1.4)
Average distance (km) to
nearest education office
Interview of the head teacher School
questionnaire
SCQ 212 85 21
(±1.9)1,2 24 (±2.8) 17 (±2.3) 25 (±3.3) 15 (±1.4)
Average distance (km) to
the food distribution
centre
Interview of the head teacher School
questionnaire
SCQ 213
60 70 (±7.5)ns 64.7
(±7.7)
77.3
(±18) 79 (±14) 60 (±3.2)
Percent of schools that
have developed a
partnership to supply
food to schools
Interview of the head teacher School
questionnaire
SCQ 216
85 39 1 50 23 40 38
Percent of schools
receiving food from
farmer groups
Interview of the head teacher. The
food received here are voluntary
contribution by the farmers / farmer
groups
School
questionnaire
SCQ
85 46 2 50 40 20 75
ns = No significant difference between gender (sex), geographical location or intervention types. 1 = Only significant difference between boys and girls. 2 Only significant difference between north and south. 3 
Only significant difference between intervention types
Annex 4: Assessment of Literacy Level using EGRA
One of the two strategic objectives (SOs) of the MGD supported Food For Education (FFE)
programme in Lao PDR is to improve the literacy of school-aged children. WFP and USDA have
identified the indicator “Percent of students who, by the end of two grades of primary schooling,
demonstrate that they can read and understand the meaning of grade level text” to measure the
reading ability of children. USDA recommended this indicator to be measured by any
assessment system (e.g. ASER, EGRA) with adequate psychometric validity and reliability. After
discussing the proposal with WFP and its implementing partners, the assessment team chose to
use Early Grade Reading Assessment (EGRA)10
, using the method and questionnaire developed
by Save the Children for their Literacy Boost programme in Lao PDR. EGRA was chosen over
other methods, as the tools/questionnaire were available to be implemented in laos without
developing the tools for Lao language (which would be beyond the scope of this baseline
survey).
A4.1. EGRA Sub-tests and Measurement Approach
EGRA was designed as a method-independent approach to measure a child’s initial reading
ability. Through a series of tests, EGRA measures various skills that are necessary building blocks
for children to read fluently and comprehend text. A summary of the various EGRA sub-tests
administered during the baseline survey and their measurement approaches are given in Table
7Table 7.
The letter knowledge sub-test used a page showing a list of 33 letters of the Lao alphabet. Pupils
were asked to say the sounds of as many letters as they could. The test was discontinued if a
pupil was unable to correctly read less than five words in the first one minute. The score for this
sub-test is the number of letters a pupil correctly named in one minute, a measure known as
correct letters per minute (CLPM). If the pupil was still reading after the first one minute, the
enumerator would continue to count the letters that the pupil read correctly, which comprised
the score for total letters correctly read (TLCR).
In the vocabulary sub-test, pupils were presented with a list of the 20 most frequently occurring
words in the students’ textbook. For this survey, the team used the words from the literacy
boost EGRA assessment developed by Save the Children Laos who had selected the words from
a list of 50 words from EGRA assessment launched in 2013. The children were asked to read as
many words as they could. Pupils who could not read at least 5 words correctly in the first one
minute were stopped and the sub-test was discontinued. The score for this sub-test consisted of
the number of familiar words read correctly in one minute (FWPM), and, for the students who
read beyond the one-minute mark, the total number of familiar words correctly read (TFWR).
 
10 During the preparation of EGRA instrument and report production the assessment team drew ideas and principals 
extensively from the Early Grade Reading Assessment Toolkit prepared by RTI for World Bank with funding from USAID. 
EGRA toolkit and relevant reports can be downloaded from www.eddataglobal.org.
70
Table 7: EGRA sub-tests and their measurement approaches
EGRA sub-test Measurement approach
Letter knowledge Number of Lao letters correctly identified. (A chart of 33 Lao letters were
shown to every pupil, who was asked to read them.)
Vocabulary Number of frequently used words correctly read. (20 commonly used
words were shown to every pupil, who was asked to read them.)
Invented-word
decoding
Number of invented words (nonsense words) correctly read. (20 invented
words were shown to students, who were asked to read them to the best
of their ability).
Oral reading fluency
and accuracy
Number of words read correctly per minute on a grade-level passage to
determine fluency. The number of words students could read correctly
from the passage, irrespective of the time it took, was served as a
measure of accuracy. (A passage was given to each student, who was
asked to read it to the best of his/her ability.)
Comprehension Number of comprehension questions answered correctly based on a
grade-level passage that the student read. If the student could not read
the passage, it was read by enumerators and the same questions were
asked to measure the listening comprehension ability.
In the invented-word decoding sub-test, students were presented with a list of 20 invented
words and asked to read as many as possible. This sub-test was administered to assess sight￾recognition skills and decoding, i.e. a child’s ability to decode and read words he/she has never
seen before. The score of this sub-test was the number of invented words read correctly per
minute (IWPM) and also total number of invented words correctly read (TIWR). Pupils who
could not read at least five invented words correctly in the first one minute were stopped and
the sub-test was discontinued.
Oral reading fluency (ORF) is a measure of both reading accuracy and speed. A child’s ORF
correlates with the skills previously discussed, since children need to have mastered letter
sounds, phonemic awareness and word reading in order to read fluently, accurately and quickly.
A child’s ORF in turn affects how well they are able to understand what they are reading. In this
EGRA sub-test, pupils were presented with and asked to read a passage, taken from the literacy
boost EGRA subtest, aloud. The final score was the number of words read aloud correctly per
minute.
The reading comprehension sub-test identified how well pupils understood the oral reading
fluency passages. After the pupil had read for one minute, the test administrator asked the child
questions pertaining to the portion of the story read. The administrator did not ask any
questions of pupils who did not read any words correctly; these pupils automatically received a
reading comprehension score of zero. For those students who were unable to read five words of
the passage within the first one minute, the test taker read the passage to the student before
71
asking the comprehension questions.
A4.2. Reliability and Validity of the Test Instruments
Internal consistency, or reliability, of the five sub-test instruments was measured by calculating
Cronbach’s alpha12F12 F12 F
11
. The results indicate a strong overall reliability. In our analysis, α = 0.84,
which is considered very good given the widely accepted threshold of α > 0.8. We also
calculated the contribution of each sub-test to the overall consistency by removing one of the
sub-tests from the model and estimating the value of α in order to make sure that each of the
sub-tests positively contributed to the overall reliability.
A4.3. EGRA Administration
The objective of the EGRA was to assess the reading skill of students after two grades of primary
schooling. Therefore, as per the USDA guidelines, only students from grade three were sampled
for the test. Before administering the EGRA test, administrators were asked to read the students
explicit information about the test and how it would be used. Pupils were asked to provide their
consent to participate in the assessment. Consent was also taken from parents and teachers
before conducting tests. The administration of the EGRA test also included a “stop” rule, which
required assessors to discontinue the administration of a sub-test if a pupil was unable to
respond correctly to any of the items at any point. This rule was applied in all EGRA tests and
was established to avoid frustrating pupils who did not understand the task or lacked the skills
to respond.
A4.4. Background Characteristics of the Sample
The background characteristics for the 830 students who took the test are summarized in Table
8Table 8, along with the pupils’ assessments of their parents’ literacy levels. Male (50 percent)
and female (50 percent) students have similar background characteristics. The average age of
the students is around eight years (9.1 years), with girls on average two months younger than
boys. A majority of the students (58.3 percent of boys and 59 percent of girls) identified
themselves as being of the Mon-Khamer ethnic group and less than one in five (17.9 percent)
students in the sample belong to the Lao/-Tai ethnic group. Most students (77 percent) do not
speak Lao at home. Results of interviews with the students show that, on average, it takes ten
minutes for the students to go to school from home (no significant difference between boys and
girls).
During the baseline survey, 58 percent of the students reported having someone at home to
help them with reading. However, only one in every five children (21 percent) take extra lessons
outside of school hours, and very few (12 percent) read extracurricular books. More than 80
 
11 Cronbach's alpha is a measure of the internal consistency of a test or scale. It is expressed as a number between 0 and 1 
and describes the extent to which all of the items in a test (in this case, the EGRA sub-tests) measure the same concept or 
construct and is connected to inter-relatedness of the items within the test. RTI considers a value of α > 0.8 to be very good for 
EGRA instruments (RTI International. Nigeria Northern Education Initiative: Results of the Early Grade Reading Assessment in 
Hausa. September 2011).
72
percent of students reported that they work at home outside of school hours, and around 60
percent help with household activities every day. Involvement in regular household activities is
significantly higher among girls than boys.
Table 8: Background demographic characteristics of EGRA pupils
Background characteristics of pupils
Percent / Mean (SE)
Total
(N=830)
Boys
(N=418)
Girls
(N=412)
Gender (sex) - 50 50
Average age (months) ns 109 (±0.6) 110 (±0.8) 108 (±0.8)
Ethnicity ns
Hmong – Eiw Mien
Mon - Khmer
Lao - Tai
Chinese - Tibetan
10.4
58.6
17.9
13.1
10.6
58.3
17.7
13.4
10.2
59.0
18.0
12.9
Language spoken at home ns
Hmong – Eiw Mien
Mon - Khmer
Lao - Tai
Chinese - Tibetan
10.4
53.0
23.4
13.3
10.6
51.3
24.7
13.4
10.2
54.6
22.1
13.1
Average distance to school (time in minutes)* 9.6 (±0.2) 9.0 (±0.3) 10.1 (±0.3)
Availability of people at home to help with reading (yes) ns 58.0 54.7 61.4
Reading extracurricular book (yes) ns 21.0 21.8 20.1
Students who take extra lessons outside school hours ns 11.6 10.3 12.9
Number of days per week that student helps with
household activities before going to school *
Never
Some days
Everyday
17.2
22.3
60.5
22.2
23.4
54.3
12.1
21.1
66.7
Number of days per week that student helps with
household activities after school hours *
Never
Some days
Everyday
17.8
20.5
61.7
22.2
21.8
56.0
13.3
19.2
67.5
* statistically significant difference between male and female
ns- no significant difference between male and female
73
A4.5. Findings from EGRA Sub-tests
Letter Knowledge:
The average scores for the letter-knowledge sub-test are presented in Table 9Table 9. Overall,
21 percent of the students could not read a single letter correctly. On average, children could
correctly read 14 letters from the list and approximately 12 letters per minute. There was no
significant difference between boys and girls. However, students from MMS schools read three
more letters correctly per minute than students from lunch schools.
Table 9: Letter recognition subtest scores (Mean ± SE) by gender and intervention type
Letter
recognition
Subtest
Intervention
type
Mean (SE) score of Letter recognition subtest
Total p-value
(N=830)
Male
(N=418)
Female
(N=412)
Correct letters
per minute
(CLPM)
MMS 13.8 (±0.5) 14.1 (±0.7) 13.6 (±0.6) 0.610
Lunch 9.2 (±0.4) 9.0 (±0.6) 9.5 (±0.7) 0.555
Total 11.7 (±0.3) 11.6 (±0.5) 11.9 (±0.5) 0.671
p-value <0.001 <0.001 <0.001 -
Total correct
letters read
(TCLR)
MMS 15.6 (±0.5) 16.4 (±0.7) 15.0 (±0.7) 0.148
Lunch 13.1 (±0.5) 13.4 (±0.7) 12.8 (±0.8) 0.548
Total 14.5 (±0.4) 14.9 (±0.5) 14.0 (±0.5) 0.216
p-value 0.001 0.004 0.034 -
Vocabulary:
Approximately, three quarters of the students (73 percent) could not identify a single common
word correctly during the baseline survey. Table 10Table 10 presents the mean scores by
intervention type and gender. On average, pupils could correctly read 3.3 words total, at a
speed of 2.9 words per minute. There was no significant difference between the performance of
boys and girls. However, mean scores again differed by intervention types. Pupils from MMS
schools could read 4.6 words on average, compared to 1.8 words for students from the lunch
schools.
Invented-word decoding:
Very few students (17 percent) could correctly identify any invented words correctly. Table
11Table 11 summarises total invented words correctly read and invented words correctly read
per minute scores by intervention type and gender. The results of this EGRA sub-test reveal that
the sample students could decode less than two words (1.5 words) from the list, on average, at
a rate of 1.3 words per minute. Scores did not vary between boys and girls; however, again,
students from MMS schools performed better students from lunch schools.
74
Table 10: Familiar word reading sub-test scores (Mean ± SE) by gender and intervention type
Familiar word
reading
Subtest
Intervention
type
Mean (SE) score of familiar word reading
subtest
p-value Total
(N=830)
Male
(N=418)
Female
(N=412)
Familiar words
per minute
(FWPM)
MMS 4.1 (±0.3) 3.7 (±0.4) 4.4 (±0.5) 0.294
Lunch 1.4 (±0.2) 1.2 (±0.2) 1.7 (±0.3) 0.165
Total 2.9 (±0.2) 2.5 (±0.3) 3.3 (±0.3) 0.051
p-value <0.001 <0.001 <0.001 -
Total familiar
words read
(TFWR)
MMS 4.6 (±0.3) 4.1 (±0.5) 5.0 (±0.5) 0.202
Lunch 1.8 (±0.2) 1.6 (±0.3) 2.1 (±0.4) 0.298
Total 3.3 (±0.2) 2.9 (±0.3) 3.8 (±0.3) 0.47
p-value <0.001 <0.001 <0.001 -
Table 11: Invented word reading subtest scores (Mean ± SE) by gender and intervention type
Invented
word reading
sub-test
Intervention
type
Mean (SE) score of Invented word reading
subtest
p-value Total
(N=830)
Male
(N=418)
Female
(N=412)
Invented
words per
minute (IWP)
MMS 1.7 (±0.2) 1.6 (±0.3) 1.8 (±0.3) 0.647
Lunch 0.8 (±0.1) 0.8 (±0.2) 0.7 (±0.2) 0.750
Total 1.3 (±0.1) 1.2 (±0.2) 1.3 (±0.2) 0.652
p-value <0.001 0.021 0.005 -
Total invented
words read
(TIWR)
MMS 1.9 (±0.2) 1.8 (±0.3) 2.0 (±0.3) 0.605
Lunch 1.1 (±0.2) 1.2 (±0.3) 1.0 (±0.3) 0.652
Total 1.5 (±0.1) 1.6 (±0.2) 1.3 (±0.2) 0.749
p-value 0.006 0.124 0.019 -
Oral reading fluency (ORF):
As illustrated in Figure 3Figure 3, 84 percent of the students could not read a single word from
connected text (paragraph), and very few (10 percent) could read at least 35 words. Only three
percent of students could correctly read at a rate of at least 35 words per minute. There were
no significant differences between boys and girls.
75
Figure 3: Fluency and accuracy of students at baseline
Table 12Table 12 summarises the TWCR and WCRM scores from the paragraph by intervention
type and gender. On average, students could read only 3.6 words per minute correctly and
could correctly identify 7.2 words from the whole paragraph. There was no significant difference
between male and female students in terms of number of correct words identified. However,
fluency of female students was slightly better than male students. There was marked variation
of scores between students from lunch and MMS schools, with MMS students reading 9.8 words
on average (accuracy) and 5 words per minute (fluency), compared to lunch students, who could
read only 4.1 words and 1.9 words per minute.
Table 12: Reading fluency and accuracy subtest scores (Mean ± SE) by gender and intervention type
Fluency and
accuracy
sub-test
Intervention
type
Mean (SE) score of reading fluency and
accuracy subtest
p-value Total
(N=830)
Male
(N=418)
Female
(N=412)
Oral reading
fluency (ORF)
MMS 5.0 (±0.5) 4.4 (±0.7) 5.7 (±0.8) 0.223
Lunch 1.9 (±0.4) 1.3 (±0.4) 2.6 (±0.7) 0.089
Total 3.6 (±0.3) 2.8 (±0.4) 4.4 (±0.6) 0.028
p-value <0.001 <0.001 0.007 -
Accuracy
MMS 9.8 (±1.0) 9.1 (±1.5) 10.5 (±1.5) 0.507
Lunch 4.1 (±0.8) 3.6 (±1.0) 4.8 (±1.2) 0.453
Total 7.2 (±0.7) 6.4 (±0.9) 8.0 (±1.0) 0.222
p-value <0.001 0.002 0.005 -
Comprehension:
As would be expected as a result of the students’ poor fluency and accuracy, reading
comprehension scores are also low (Table 13Table 13). On average, pupils could answer only 0.5
76
questions correctly. There was no statistically significant difference by gender. As mentioned
previously, very few children were able to read the passage to themselves, so most were tested
for listening comprehension. On average, students could answer 1.6 listening comprehension
questions correctly. There was no significant difference by sex, but students from lunch schools
demonstrated slightly better listening comprehension than students from the MMS schools.
Table 13: Comprehension subtest scores (Mean ± SE) by gender and intervention type
Comprehension Intervention
type
Mean (SE) score of comprehension subtest
Total p-value
(N=830)
Male
(N=418)
Female
(N=412)
Reading
Comprehension
MMS 0.7 (±0.1) 0.6 (±0.1) 0.8 (±0.1) 0.462
Lunch 0.3 (±0.1) 0.2 (±0.1) 0.3 (±0.1) 0.279
Total 0.5 (±0.1) 0.4 (±0.1) 0.6 (±0.1) 0.150
p-value <0.001 0.002 0.008 -
Listening
Comprehension
MMS 1.3 (±0.1) 1.2 (±0.1) 1.3 (±0.1) 0.551
Lunch 2.0 (±0.1) 2.1 (±0.2) 1.8 (±0.2) 0.338
Total 1.6 (±0.1) 1.7 (±0.1) 1.6 (±0.1) 0.562
p-value <0.001 <0.001 0.028 -
Looking at the relationship between ORF and comprehension offers further insight as to how
children learn and shows the link between accuracy, fluency and comprehension (Figure 4Figure
4). It is clear that reading comprehension is highly correlated with reading fluency and accuracy.
These results are in line with the underlying assumption that students who can read with
accuracy and speed can also better understand the meaning of the text.
Figure 4: Mean reading comprehension scores (number of correct answers given) against mean fluency and
accuracy (number of words correctly read by students)
The baseline survey classified students into three tiers: emergent (non-readers), beginning, and
77
reading with comprehension based on their reading comprehension skills. As per the literacy
boost classification style, students with reading comprehension scores greater than 75 percent
were classified as readers with comprehension. This was the indicator used to assess the
percentage of students who can read and understand grade level text.
Figure 5Figure 5 shows the reading comprehension skills by intervention type. In this sample, we
see that 90 percent of students at MMS schools and 96 percent of students at lunch schools are
non-readers and thus have very low reading and comprehension skills. On average, only two
percent of the students could read with a comprehension level of at least 75 percent. Students
from MMS schools performed slightly better than students from lunch schools at baseline.
Although this difference is statistically significant, it is not practically meaningful.
Figure 5: Baseline reading with comprehension tiers by intervention type
78
Annex 5: Dietary Diversity Data and Analysis
Dietary diversity was used to measure the of quality school-age children’s diets in WFP
supported schools. It is assumed that the FFE programme will have an effect on dietary diversity
through the provision of school meals and by increasing children’s and families’ knowledge of
child health and nutrition.
Volume 11 of the Feed the Future (FTF) Guidance Series (Feed the Future, 2014) was used to
inform and guide the process of measuring dietary diversity during the baseline survey. Data
was collected through interviews with parents. Food consumption patterns and dietary intake
were measured using a 24-hour recall period. Parents were asked if the child had consumed any
of the 19 listed food items during the previous 24 hours. If the amount was less than one
teaspoon, the response was counted as not having been consumed. These responses were later
converted into ten food groups, identified by the FTF guidance document:
1. Grains, roots and tubers
2. Legumes and beans
3. Nuts and seeds
4. Dairy products
5. Eggs
6. Flesh foods including organ meat and miscellaneous small animal protein
7. Vitamin A-rich dark green leafy vegetables
8. Other vitamin A-rich vegetables and fruits
9. Other vegetables
10. Other fruits
Individual dietary diversity scores (DDS) were calculated by combining the number of food items
consumed across these ten food groups.
79
Table 14Table 14 shows the consumption frequencies for all 19 food groups, while Table
15Table 15 shows the aggregated consumption frequencies for the ten FTF food groups.
More than 92 percent of parents reported that their childstudent consumed grains, roots and
tubers as staple foods, while a quarter (27 percent) of them had consumed legumes and beans
during the previous 24 hours. Only one in every five children (20 percent) consumed milk or
dairy products and almost half had consumed eggs (46 percent). Four out of every five students
had consumed flesh foods (82 percent). Three quarters of the students had consumed vitamin A
rich dark green vegetables (73 percent), and half had consumed other vitamin A rich vegetables
and fruits (51 percent). There were no significant differences between boys and girls.
80
Table 14: Food item consumption frequencies
SL Food items
Percent
Total
(N=810)
Boys
(N=430)
Girls
(N=380)
1
Food made from grains, such as bread, rice, noodles,
porridge 90.5 90.2 90.8
2
White potatoes, white yams, manioc, cassava, other
local root crops or any other foods made from roots 23.3 21.2 25.8
3 Any foods made from beans, peas, or lentils 26.9 27.9 25.8
4 Any foods made from nuts or seeds 24.1 22.8 25.5
5 Milk 11.4 11.2 11.6
6 Cheese, yogurt, or other milk products 14.1 13.3 15.0
7 Eggs 46.4 45.3 47.6
8
Any liver, kidney, heart, or other organ meats from
domesticated animals, such as cattle, swine, goat,
chicken, or duck
12.8 13.5 12.1
9
Any liver, kidney, heart, or other organ meats from wild
animals 4.6 4.9 4.2
10 Any meat, such as beef, pork, lamb, goat, chicken, or
duck 49.0 50.2 47.6
11 Any flesh from wild animals 18.0 18.4 17.6
12 Fresh or dried fish, shellfish, or seafood 46.5 47.9 45.0
13 Grubs, snails or insects 12.3 13.3 11.3
14 Any dark green leafy vegetables 72.7 75.3 69.7
15 Pumpkin, carrots, squash, or sweet potatoes that are
yellow or orange inside 40.5 42.8 37.9
16 Ripe mangoes, ripe papayas or other local vitamin A-rich
fruits 18.9 19.3 18.4
17 Foods made with red palm oil, red palm nut, or red palm
nut pulp sauce - Vitamin A rich 1.4 1.4 1.3
18 Any other vegetables 72.2 70.2 74.5
19 Any other fruits 11.5 11.6 11.3
No statistically significant difference between boys and girls
81
Table 15: Consumption frequencies for the ten FTF food groups
SL
Food items (10 FTF food groups) Percent
Total Boys Girls
1 Grains, roots and tubers 92.3 92.1 92.6
2 Legumes and beans 26.9 27.9 25.8
3 Nuts and seeds 24.1 22.8 25.5
4 Dairy products 20.4 19.3 21.6
5 Eggs 46.4 45.3 47.6
6
Flesh foods including organ meat and misc. small animal
protein 82.1 84.2 79.7
7 Vitamin A-rich dark green leafy vegetables 72.7 75.2 69.7
8 Other vitamin A-rich vegetables and fruits 51.1 53.7 48.2
9 Other vegetables 72.2 70.2 74.5
10 Other fruits 11.5 11.6 11.3
No statistically significant difference between boys and girls
The average dietary diversity score of pupils was approximately 5.0 out of 10 (Table 16Table 16).
There was no statistically significant difference between boys and girls. However mean scores
varied significantly by intervention type and province. Students from MMS schools have a
slightly higher DDS than students from lunch schools. When disaggregated by province, Luang
Namtha had the highest DDS (6.1) and Sekong had the lowest (3.2).
Table 16: Mean DDS by sex, intervention type, and province
Mean dietary diversity score (SE)
Total Boys Girls
Overall dietary diversity score 5.0 (±0.06) 5.0 (±0.09) 5.0 (±0.09)
Intervention type a
Mid-morning snacks (MMS) 5.3 (±0.09) 5.5 (±0.13) 5.1 (±0.13)
Lunch 4.7 (±0.08) 4.5 (±0.11) 4.9 (±0.13)
Province b
Pongsaly 5.3 (±0.24) 5.7 (±0.36) 5.0 (±0.32)
Oudomxay 5.0 (±0.09) 5.1 (±0.18) 4.8 (±0.12)
Luang Namtha 6.1 (±0.20) 5.9 (±0.28) 6.2 (±0.29)
Salavan 5.3 (±0.13) 5.1 (±0.17) 5.5 (±0.19)
Sekong 3.2 (±0.09) 3.2 (±0.12) 3.2 (±0.13)
Attapeu 5.8 (±0.17) 5.8 (±0.22) 5.9 (±0.27)
a. Statistically significant difference between intervention types
b. statistically significant difference between provinces
82
The level of dietary diversity was assessed by categorising the score for each child. Two
approaches were used. In the first, students’ scores were divided into three groups: low dietary
diversity (DDS≤3), medium dietary diversity (DDS between 4 and 6), and high dietary diversity
(DDS≥7). In the second, only two classifications were used: DDS<5 and DDS≥5. The results of this
analysis are given in Table 17Table 17.
The baseline survey found that around one in five children (21 percent) had had a high DDS, and
a similar number had a low DDS (22 percent). Most students (57 percent) had medium DDS.
Overall, 58 percent of students had consumed at least five different food items during the last
24 hours. There was no significant difference between the results for boys and girls; however
students from MMS schools show significantly …………..dietary diversity than those from lunch
schools.
Table 17: Dietary diversity status of pupils by sex and intervention type
Dietary diversity category
Total (%) Sex (%) Intervention (%)
Boys Girls MMS Lunch
Three groups
Low Dietary Diversity (1-3) 22.1 22.4 21.8 16.4 28.1
Medium Dietary Diversity (4-6) 56.5 54.8 58.4 56.0 57.0
High Dietary Diversity (7-10) 21.4 22.8 19.7 27.5 14.9
Two groups
DDS < 5 42.3 40.6 44.2 36.2 48.6
DDS ≥ 5 57.7 59.4 55.8 63.1 51.4
No statistically significant difference between boys and girls
Statistically significant difference between intervention types (MMS / Lunch)
83
Annex 6: Teacher Training History and Background
Training teachers on new and quality teaching techniques and tools had not begun when the
baseline survey was conducted. As such, it was agreed that teachers would be asked about
previous in-service or on-the-job training rather than training received through the programme.
Data on teachers’ training was collected for all of the teachers in the sample schools (579
teachers) using the school questionnaire and interviews with the head teacher. This data was
verified through interviews with teachers. Detailed findings are presented in Table 18Table 18.
Table 18: Background characteristics of teacher and training history
Background characteristics of teachers Mean (SE) or percent
Total Male Female MMS Lunch
Percent of female teachers 2 57 - - 62 50
Age (years)
Mean age 1,2
Age groups 1,2
<30 years
30-45 years
>45 years
31
(±0.3)
53
40
7
34
(±0.6)
35
54
11
29
(±0.4)
66
31
3
32
(±0.4)
48
44
8
30
(±0.5)
59
36
6
Educational qualification ns
Bachelor
Higher diploma
Technical/ vocational diploma
Higher secondary and others
0.9
31
67
0.9
0.4
29
69
1.6
1
33
66
0
0.9
30
68
0.9
0.8
33
66
0.4
Teaching experience (years)
Average years of teaching experience
1,2
Experience categories 1,2
<5 years
5-10 years
>10 years
9.9
(±0.3)
28
37
34
12 (±0.6)
22
33
45
8.5
(±0.4)
33
41
26
11
(±0.4)
24
37
39
8.9
(±0.5)
34
38
28
Experience of the head teacher ns 17
(±1.0)
16
(±1.0)
17
(±2.6)
17
(±1.4)
16
(±1.3)
Training history
Safe food preparation and storage
practices 2
Commodity management 2
Teaching/learning techniques ns
Training on school meal program 2
Health hygiene and nutrition ns
7.7
6.2
23
7.0
15
8.9
8.1
20
8.1
14
6.7
4.9
26
6.1
16
3.7
2.2
26
2.2
12
13
12
20
13
18
ns No significant difference between gender (sex) or intervention types. 
1 Only significant difference between boys and girls. 
2
Only significant difference between intervention types. 
1, 2 significant difference between both gender (sex) and intervention
types.