“schooling‐as‐usual,” but often, those same programs did not work for boys either. For example, technology interventions – whether substituting teachers with computers or providing students with laptops – did not help improve learning (Linden 2008; Sharma 2014). Although there are teacher professional development programs that work to improve student learning (Popova et al. 2018), our findings demonstrate that introducing new pedagogical methods through a short teacher training program is less likely to be effective to improve girls’ learning; and this is true no matter which education level the intervention targets (Berlinski and Busso 2017; Yoshikawa et al. 2015). In addition, school accountability interventions such as distributing school report cards to students and parents were not effective for girls, either in Sri Lanka or in Liberia (Aturupane et al. 2014; Piper and Medina 2010b).

# 5. Discussion

## Inequality

Up until this point, this paper has focused on identifying the interventions that deliver the highest absolute learning gains for girls. An alternative approach would be to identify those programs that benefit girls most relative to boys. In other words, this approach would focus on closing inequalities (or increasing them, in contexts where girls are ahead in school) rather than merely improving girls’ access and learning without regard to boys’ performance. Figure 11 shows the gains in access and learning for boys and for girls. The programs with the most unequal impacts – both favoring girls and favoring boys – are general interventions. Almost all of the girl‐targeted interventions for which we have data on both girls and boys have similar results for both genders, with slightly better results for girls. 11 in 20 girl‐targeted studies do not report outcomes for boys. If one’s objective were purely inequality reduction, then cash transfers in South Africa had dramatically larger access impacts on girls than on boys, despite not being gender‐targeted (Eyal, Woolard, and Burns 2014). A mother tongue learning instruction in Kenya in the Lubukusu language had no discernible impact on boys’ learning but a sizeable impact for girls (Piper, Zuilkowski, and Ong’ele 2016). However, there are no clear patterns as to which classes of interventions are inequality enhancing versus inequality reducing. For this inequality analysis, we drop girl‐targeted studies that do not report impacts for boys. If one were to assume that those girl‐targeted studies that did not report outcomes for girls had zero impact on boys, then girl‐ targeted interventions would decrease inequality more than general interventions.

## Costs

While we standardized effect sizes across interventions in this review, incorporating cost data would enhance the analysis, as the most effective programs may not be the most cost‐effective and therefore not easy to scale up. However, despite a strong demand for cost data, few studies report them. McEwan (2015) in his review stated that 56 percent of studies reported no cost details, and most of the rest reported minimal information. We encountered similar problems when we tried to collect cost data. In addition, even when cost data are reported, they are often not comparable due to different accounting methods. Taking an early childhood development program in rural Mexico as an example, the cost per child estimated by World Bank researchers was $76 (Cárdenas, Evans, and Holland 2015), but when evaluated by another group of researchers at Brookings, the cost per child almost doubled to $174‐$202 (Gustafsson‐Wright, 13