High- and low-performing schools: How can countries narrow the gaps?

of schools also retains teachers who are, on average, older by about four years and more likely to be female by 40 percentage points.

What may be driving differences in school performance?

Comparing high- and low-performing schools, tables A.7 and A.8 in appendix A highlight the specific teacher characteristics and school inputs that appear to distinguish the highest-performing schools most clearly from schools at the bottom of the distribution. Among inputs, lower pupil-teacher ratios in top-ranking schools are a salient distinguishing factor, with high-performing schools having 20 fewer students per teacher on average, as published evidence would lead one to predict (Chetty et al. 2011).20 But simpler inputs, such as the presence of functioning blackboards and clean, private, gender-separated toilets also appear to play a role. The analysis also shows substantial differences in teacher test scores between high- and low-performing schools, an intuitive result. But striking differences also emerge concerning the gender and age composition of the teaching workforce. The following section explores these key differentiating factors in detail. Doing so suggests entry points for policy to reduce performance gaps between these groups of schools.

The comparison of highest- and lowest-performing schools yields findings that can inform policy to boost performance among lagging schools. Some basic school inputs are particularly scarce in low-performing schools, which suggests that, once in-person learning resumes, governments have room to make meaningful improvements with simple solutions that matter for learning outcomes.

SDI results contain information helpful for targeting interventions to improve school inputs. For instance, it is possible to look at how many schools by country or by urban-rural setting have some essential features or “minimum inputs” to operate efficiently. Minimum inputs are defined here as having functioning blackboards, private and gendered toilets, and a pupil-teacher ratio below 35. Across SDI countries, only 20 percent of rural schools possess these minimum school inputs, and 35 percent of urban schools meet this basic standard. Thus, in some settings, targeting rural schools early for additional inputs could deliver results. In some countries, SDI data on school inputs may serve as a more generalized wake-up call to decision-makers. In Togo and Niger, for example, only 2 percent and 8 percent of all schools, respectively, have the minimum school inputs as measured by SDI surveys.

SDI results point to tangible actions for in-person learning that policy makers can take to address school inputs. Yet caution is warranted, because