Academic journal article Asian American Policy Review

Advancing the Asian American and Pacific Islander Data Quality Campaign: Data Disaggregation Practice and Policy

Academic journal article Asian American Policy Review

Advancing the Asian American and Pacific Islander Data Quality Campaign: Data Disaggregation Practice and Policy

Article excerpt

Abstract

This study examines the impact of disaggregated data on shaping programs, services, and improving student outcomes for Asian American and Pacific Islander (AAPI) student populations at Coastline Community College (CCC). Using a mixed methods approach, including institutional data analysis and semi-structured staff interviews to examine the Asian American Native American Pacific Islander--Serving Institutions (AANAPISI) program and its use of disaggregated data to inform programmatic implementation and decision making, our findings indicate that disaggregated data largely shapes and improves the planning, implementation, and delivery of services to specific ethnic groups in order to enhance student experiences and outcomes.

Introduction

Decades of publications focusing on the Asian American and Pacific Islander (AAPI) student population have called for the collection and reporting of disaggregated data as a necessary tool for more accurately representing and understanding who students are, how they are performing, and how institutional student services can become more effectively targeted. (1) These publications cite the major differences that exist across various ethnic groups within the AAPI population as rationale for collecting more granular data. (2) These concerns continue to be the motivation for AAPI data disaggregation efforts in the twenty-first century. The National Commission on Asian American and Pacific Islander Research in Education (CARE) reports that data disaggregated for individual subgroups--by race, ethnicity, gender, and other demographic distinctions--is critical for raising awareness about issues and challenges that impact subgroups disproportionately. (3) The aggregation of data on AAPIs in higher education research, policy, and practice obscures the tremendous diversity that exists within the larger AAPI category. (4) In reality, the AAPI population consists of at least forty-eight ethnic groups that differ greatly in cultural backgrounds, historical experiences, and socioeconomic and educational circumstances. (5)

As colleges and universities face increased concerns about accountability from internal and external constituents, data is an important tool for informing the work of practitioners and policy makers, which would allow them to target resources where they are most needed and to more effectively support an increasingly complex and heterogeneous student population. In order to improve data quality to more accurately represent and serve AAPI students, institutions must be supported by federal data policies; however, tangible change primarily occurs through the localized efforts of campuses and community groups. Thus, this paper aims to: (1) showcase the demonstrated success of data disaggregation efforts for improving AAPI student outcomes at a two-year institution; and (2) use this model to provide rationale for the advocacy of more localized data disaggregation efforts, as well as political support from federal data policy.

Calls for AAPI Data Disaggregation

The need for disaggregated data that better represents the heterogeneity in the AAPI population is not a new concept. In fact, as early as 1980, before "disaggregated data" was widely used as a phrase, scholars were already pointing to the problem of lumping Asian Americans from different ethnic and cultural groups together into one category. (6) Over three decades later, this issue is still at the forefront of the AAPI agenda in public health, social welfare, and civil rights. (7) The aggregation of AAPI ethnic groups in data collection and reporting remains a prominent issue across all public sectors. The limited disaggregated data that is available reveals a startling reality. Median household income, for example, shows that although some ethnic subgroups, Asian Indians in this case, earn up to $22,000 over the median household income, Southeast Asians earn between $14,000 and $22,000 below the median. …

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