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Due to school choice initiatives and other factors related to current educational policies, more students are able to attend schools outside of their neighborhood. This suggests that not all financial, social, and human capital resources available to the student come from the family. This trend calls for incorporating neighborhood and school SES information as vital components in an expanded measure of SES. Furthermore, one of the four major recommendations made by the NAEP SES Expert Panel (2012) suggests researchers to consider the development of an expanded SES measure that includes neighborhood and school SES variables and possibly explore data from various sources to link to NAEP datasets in order to provide more accurate estimates of student socioeconomic background. The purpose of this paper is to explore various data sources and weighting schemes for forming an expanded composite SES measure by incorporating neighborhood and school SES-related information as possible SES components along with the current NAEP SES-related proxy questionnaire items.
Neighborhood SES can be defined as factors that relate to the greater community context in which an individual student resides. These factors may include specific information about the average education level of adults by age groups living within the community, the average price of the houses, the percentages of housing rentals and ownerships, the median family or household income in the neighborhood, various types and numbers of material possessions in a household (i.e. cars, digital devices, major appliances), availability of public libraries, as well as access to parks and museums. The rationale for including neighborhood SES information in an expanded measure of student SES is that resources that support students’ learning and development may be available through different sources other than individual students’ family alone.
Although many students attend schools in the neighborhood in which they live, more students are able to attend schools outside of their neighborhood due to school choice initiatives and other factors related to current educational policies. This could pose differences between neighborhood SES in which students reside and the SES composition of the schools that students attend. NAEP currently measures school SES on two aspects: the percentage of student eligibility for NSLP and Title 1 status. There could be other factors that relate indirectly to school SES and relevant for sending messages about academic expectations. NAEP school questionnaire items about availability of digital devices and technology resources, professional development programs for teachers, and advanced courses could indicate the degree of financial resources a school may have to support its students’ academic achievement.
Guided by these constructs about neighborhood and school SES factors, this paper explores various data sources, such as the Bureau of Labor Statistics and the U.S. Census Bureau, to link to current NAEP SES-related proxy items. Cluster analysis and multilevel modeling of the student-level, neighbor, and school SES constructs on student achievement are conducted to examine the feasibility of an expanded SES composite measure. Various weighting schemes are examined to create a more comprehensive picture of the expanded SES construct.