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Traditional ways of measuring educational proficiency, based on assessment results and the percentage of children enrolled in schooling, may not be as effective a measurement while COVID-19 impacts upon attendance rates.

Analysts working with SDG indicators on learning proficiency, in particular Indicator 4.1.1, would in many cases be familiar with a formula such as the following:

The percentage of enrolled learners who are proficient,听S, is typically known from assessment results. The percentage of children of the age of the grade in question who are not enrolled,听N, is typically known from household data.听P听is what planners are ultimately interested in: the percentage of the relevant age cohort听in the population听who are proficient. While there is some ambiguity over whether Indicator 4.1.1 refers to听S听or听P,听P听is clearly important and must be monitored.

The above formula assumes that non-enrolled children do not reach minimum proficiency levels, following the approach taken in听UIS (2020)听and听UIS (2017). The relationships can be illustrated as in the following graph, which is based loosely on levels of learning proficiency and the out-of-school problem in developing countries. Here听P听is a function of听S听and听N, according to the above formula.听

In the context of COVID-19, sudden declines in enrolment, meaning听N听rises, and declines in proficiency in the population due to disruptions in schools, meaning听P听drops, are possible. In examining the effects on the three statistics听P,听N听and听S, it is important to remember that听N听and听S听influence each other. Assuming that children who drop out of the schooling system are the academically weakest learners, an assumption that is likely to hold for a number of reasons, one can expect听S听either to rise or decline, depending on the magnitudes of the two effects: dropping out of school and learning losses. If one has estimates of听P听and听N, then the new听S听is calculated according to the following transformation of the previous formula:

To illustrate the ambiguity, we can imagine learning losses resulting in a drop in听P听from the 35% seen in the graph to 33%. If out-of-school听N听increases from 5% to 9%,听S听declines from 37% to 36%. However, if听N听displays a larger increase, from 5% to 13%, then听S听displays an听increase听from 37% to 38%. Even with learning losses in the population of a specific age, if enough learners drop out, and we assume that these learners are those who struggled most academically, then assessment systems may in fact detect an increase in the percentage of proficient learners.

Clearly, planners need to be fully aware of these relationships.听Above all, the first formula above should not be used to conclude that more out-of-school children on its own produces a decline in P.听If听S听was 37% (as in the graph) and then out-of-school听N听increases from 5% to 13%, one cannot conclude that听P听drops to 32%. This would ignore the fact that if听N听changes,听S听automatically changes too.听

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