determinant of learning is age for grade, a proxy indicator for students who may have repeated one or more years in school.

These findings linking learning outcomes with exogenous factors at the individual level have also been confirmed in Argentina. Recent evidence using standardized testing data (including PISA, LLECE, and Argentina’s national standardized test, _Operativo Nacional de Evaluación, ONE_ ) have found that socioeconomic background and individual characteristics, such as attending preschool and not repeating grades, are hugely important in determining learning outcomes in students (Albornoz, Furman, Podesta, Razquin, and Warnes, 2015, Marchionni, Pinto, and Vazquez, 2013, Fresoli, Herrero, Giuliodoli, and Gertel, 2007, and Kruger, 2011).

# _2.1 School Characteristics_

A recent meta review of studies and impact evaluations in developing countries finds strong evidence that textbooks and other similar materials increase student learning, as do basic furniture such as desks, tables, and chairs, and characteristics of the school buildings themselves. Importantly, there is some evidence that students in the bottom of the performance distribution are most affected by poor school conditions (Fertig and Schmidt, 2002). The availability of electricity also has a strong effect (Glewwe, Hanushek, Humpage, and Ravina, 2014). While the presence of computers on their own doesn’t seem to generate an impact, computer-assisted learning programs have proven effective when instruction is integrated into the curriculum and tailored to individuals, and where teachers are well prepared to support the students (Evans and Popova, 2015). The availability of computer facilities and science laboratories is also significantly correlated with better learning outcomes in Mexico (De Hoyos, Espino, and García, 2012).

Evidence from Argentina is consistent with these findings. Educational resources such as libraries, multi-media resources, science laboratory equipment, facilities for the fine arts, and computers were all found to be correlated with higher test scores (Fuchs and Wößmann, 2004, and Santos, 2007), although school infrastructure was found to be less important (Santos, 2007).

Among the most potentially influential factors leading to learning are teachers and school directors. Recent work in the United States underlines both the tremendous impact teachers can have, as well as the great variance of the performance among teachers, and the lasting consequences this can have on students. Students lucky enough to have great teachers can gain 1.5 grade levels or more, while students with poor teachers can end up mastering only half or less of the curriculum (Hanushek and Rivkin, 2010). Research from developing countries also corroborates the singular potential impact of teachers: Glewwe et al. (2014) find that, of 63 studies estimating the effect of teacher experience, 43 show no statistically significant impact. But of the 20 that do show an impact, 17 of them are positive. The evidence for teacher education is slightly stronger, as is the evidence for teachers’ knowledge of subject matter. As with computers, the evidence seems to indicate that effective interventions by teachers should be tailored to their skill level and provide them with specific guidance and support in their teaching (Evans and Popova, 2015).

Recent evidence from Latin America also points to the strong effect of the quality of teachers on learning outcomes. Using 2006 SERCE data, Bruns and Luque (2014) show that, within the same schools, large variations exist in student learning outcomes between classrooms, accounting for more than 40 percent of the total variation in Nicaragua and Cuba. Although these measures probably reflect policies of streaming children by ability into different classrooms, such large learning gaps are revealing of how being assigned to different teachers influences student 4