The purpose of the study is to examine gender and inclusion differences in education, and to suggest policy actions as well as future analytical and operational work to address these differences.

# 2. Methodology

The research design for the study was informed by several sources of data. Data examination of the National Social-economic Household Survey (Susenas), the National Labor Force Survey (Sakernas), Dapodik, EMIS, and the 2010 Population Census was conducted to collect gender-disaggregated data on student enrollment rates, and the composition of teacher and administrative staff in the workforce, as well as disability information. This review and analysis of existing data sources allowed for the identification of areas of subnational gender variation in education attainment and other indicators.

Susenas collects data at the household and individual levels on many aspects of social and economic characteristics, such as: consumption, labor, health and other household variables. Sakernas is a survey that is specifically designed for labor data collection. Both Susenas and Sakernas are nationally representative surveys conducted by BPS ( _Biro Pusat Statistik_ /Central Bureau of Statistics) and used by the government for national planning documents. The population census, also conducted by BPS, records the number, composition, distribution, and selected characteristics of the population with national coverage.

Administrative data used in this study is the MoEC’s Dapodik and the MoRA’s EMIS. Dapodik records selfreported information on: (i) school-level data (public-private, ownership status, establishment date, accreditation status, availability of Internet, the number of school facilities and their condition); (ii) student-level data (sex, learning groups, parents’ information); and (iii) teacher-level data (sex, employment status, certification status, education qualification). EMIS records data on Islamic schools under the MoRA, including: number of students (data available by grade depending on the published year), number and condition (good, mild-/medium-/heavy- damaged) of school facilities such as classrooms, library, laboratories (computer, science, language), ownership status (public/private), and official instructional hours. Data reliability of Dapodik and EMIS is still an issue due to large variation in school operators’ competency in managing the data system and the lack of a verification mechanism. Nevertheless, local governments use Dapodik and EMIS in their planning documents as well, because they are the only administrative data available at the school level.

Based on a desk review, districts were identified for a deeper dive to conduct the qualitative analysis to better understand gender gaps in education. Districts were selected based on existing gender gaps in enrollment at different levels of education, coupled with data on adult literacy rates, school completion rates and reports on child marriage. Field visits were conducted to selected districts in two provinces to uncover drivers of gender differences, as well as issues of social inclusion, and to explore policy approaches to improve learning outcomes and educational achievement for all children. Interviews were held with local government education officers, MoRA provincial-level and district-level education officers, and school and _madrasah_ principals. During school and _madrasah_ visits, focus group discussions were held with supervisors, teachers, parents and students. Interviews were also held with several MoEC and MoRA officials in the central government, as well as an official from the Ministry of Women’s Empowerment and Child Protection (MoWECP).

There were some limitations that impacted the district selection for field visits. A number of provinces were off limits due to natural disasters, such as the earthquake and tsunami in Sulawesi, and areas that were difficult to reach, such as Nusa Tenggara and Papua. With these constraints in mind, the provinces of East Java and South Kalimantan were selected.

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