22. Attendance Rate | |||||||||
VERSION | V5.0 - 2026.03 — Existing | ||||||||
INDICATOR CODE | 22 | ||||||||
TECHNICAL OWNER | SBP | ||||||||
INDICATOR TYPE | Country Level Outcome Indicator | ||||||||
INDICATOR CLASSIFICATION | Complementary | ||||||||
INDICATOR SCOPE | Programme specific | ||||||||
APPLICABILITY | The selection of this indicator is recommended against the following sub-activities in CSPs logframes. Selection of the below sub-activities will NOT trigger the mandatory selection of this indicator:
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UNIT OF MEASUREMENT & ANALYSIS | Percentage of students | ||||||||
DEFINITION | The indicator is defined as the overall average percentage of female and male students | ||||||||
RATIONALE | Increased access to education and improved learning outcomes of girls and boys are two of the main outcomes for schoolchildren laid out in WFP’s school feeding theory of change. Regular school attendance is a key factor for improved education outcomes, and School Feeding Programmes serve as an incentive for children to attend school. Measuring the percentage of students that actually attend school out of the total number of students enrolled is a way to measure the impact of School Feeding Programmes beyond just school enrolment. In addition, some aspects of school feeding (e.g., take-home rations) can be designed with conditionality of school participation, mainly attendance, attendance monitoring is prerequisite to receiving the ration. | ||||||||
DATA COLLECTION TOOL | Data is to be collected from school records. Electronic or paper-based records are available at schools or centrally at the Ministry of Education. This data is available at schools and WFP must compile this information on annual basis at the end of each school year. SBP is piloting School Connect in 26 countries as of 2025. School Connect is a digital data management information system collecting data at school level. For more information or specific support on data collection tools consult SBP MERL team. | ||||||||
SAMPLING REQUIREMENTS | No sampling required. Data should be collected at all schools assisted by WFP. If CO is unable to collect data from all schools, contact SBP MERL team for further guidance. | ||||||||
INDICATOR CALCULATION FOR REPORTING | This indicator is calculated by the following steps: Annual average percentage of students attending school over students enrolled = (Xi / Yi) x 100% Where:
And: Xi = (X1 + X2 + X3 + … + Xn) / Yi Where:
…
And: X1 = X1.1 + X1.2 + X1.3 + … X1.z / Y1 … Xn = Xn1 + Xn2 + Xn3 + … Xnz / Yn Where:
…
… (Repeat for months 2 – n)
…
Alternatively, if attendance is not recorded daily in schools, and/or data collection/access is not possible, the average number of students attending any given month (X1, X2, … Xn), can be captured through a randomized school visit and headcount on a given day of the month. This should be noted in data notes to account for possible biases in the data. | ||||||||
DATA ENTRY AND DISAGGREGATION IN CORPORATE SYSTEMS | The following elements are mandatory in the combination entered in COMET for this indicator.
The attendance rate has to be entered on COMET based on the following disaggregation: sex, overall value (as per below table).
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BASELINE | Baselines are established only once for the entire CSP. They remain fixed for the full CSP period unless otherwise specified. Baselines must be set using data collected within three months before or after the start of the activity. If no baseline is established within this three month window, the first collected value will serve as the baseline. If a new CSP begins and the activity continues from the previous CSP, the last reported value from the previous CSP becomes the baseline for the new cycle. Note: Any change in target, location, and/or modality that creates a new reporting combination for an existing indicator requires a separate baseline. | ||||||||
TARGET SETTING | Annual targets: Context specific. End of CSP target: Context-specific. Ideally, a School Feeding Programme should aim at improved attendance rates; in food security crises, the target could be the maintenance of the attendance rate and to avoid any reduction. | ||||||||
FREQUENCY OF DATA COLLECTION | Attendance records are usually kept by schools and then these records are accessed by WFP or CPs. Data can be collected every day of the month if the CO and the schools have the needed systems to capture this data. In some cases, WFP can be tracking attendance daily and directly, if schools in that CO are using school connect or any other attendance tracking system. These systems can be used to collect attendance data, and the proper validation and verification mechanisms should be put in place (randomized visits, monitoring exercises, etc.). In the contexts where attendance records are not available daily, or WFP cannot access them, or any other challenge in data collection/access exists, data could also be collected once a month through a randomized head count of children in school on a specific day (see below). | ||||||||
INTERPRETATION | It is expected that school feeding incentivizes regular attendance to school, so that school children can learn and also access school health and nutrition services to be well nourished and healthy. The higher the percentage of children attending school over the total number of students enrolled each year, the more effective School Feeding Programmes are at keeping children in schools and at increasing access to education and improved learning for schoolchildren. When interpreting results, always refer to planned versus actuals, and analyse/explain reasons for target shortfalls or surplus, or for meeting targets. An attendance rate of 100% means that all students enrolled attended school every day, and thus, that the School Feeding Programme could improve and/or maintain access to education. To put the indicator into perspective, it will be important also to report on trends from previous years and on any potential external factors, which may have a positive or negative effect on school attendance. Pipeline breaks affecting food distribution may affect monthly school attendance, along with other external factors, as such it is recommended to analyse month by month results along with output situation. It is important to highlight any fluctuations and the rationale for these in the annual country reports and to stipulate if these fluctuations are related to the provision of/ non-provision of school feeding. | ||||||||
REPORTING EXAMPLE(S) |
As per the table above, the average attendance rate is 81% for the school year 2020-2021 with lower attendance noted in the lean season of country X in the months of February, March, and April. Monthly variances between the attendance of boys and girls were noted with more boys attending school on monthly basis than girls. Results were further investigated and the main reason behind girls not attending school regularly was to help in household chores. Age differences were also noted with older girls and boys (10-14 years old) more likely to skip school to support the household income generation. | ||||||||
INDICATORS COLLECTED & ANALYSED AT THE SAME TIME |
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COMPLEMENTARY QUALITATIVE RESEARCH | This indicator can be complemented by many types of qualitative research to provide more insights into programme implementation and results achieved. Below are examples of topics that can be explored but other avenues are also possible based on CO interest and implementation:
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DECISIONS DATA CAN INFORM | This indicator can support many CO level decision, below are some suggestions:
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VISUALIZATION |
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LIMITATIONS | Several limitations exist for this indicator:
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FURTHER INFORMATION | Consult the CHQ SBP team. | ||||||||
22. Attendance Rate
- Published on Apr 13, 2026
- 7 minute(s) read
