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Dual Enrollment in Rural Areas: Understanding Access and Participation

Region:
Central
Abstract:

Description: One well-established strategy for improving college readiness and success is dual enrollment, which allows secondary students to take college courses and earn college credits. Dual enrollment programs may be especially important for rural students, whose college-going rates lag behind those of their more urban peers. Although dual enrollment programs are common, stakeholders lack a comprehensive resource for understanding what is known about access and enrollment in their states. This study is designed to address regional needs by providing detailed information about dual enrollment access and participation within and across REL Central states.

Research Questions:

  1. What are the rates of dual enrollment access and student participation in REL Central states, for the REL Central region, and across the nation?
  2. Do dual enrollment access and student participation vary by school poverty level and school locale (city, suburb, town, or rural area)?

Study Design: REL Central will use publicly available, school-level data from the Civil Rights Data Collection and the Common Core of Data from the 2015/16 academic year. Quantitative analyses will focus on descriptions of access to and participation in dual enrollment across the REL Central region. To address research question 1, REL Central will calculate the rates of dual enrollment access and participation for each REL Central state, for the entire region, and for the nation. To address research question 2, REL Central will calculate rates of dual enrollment access and participation, disaggregated by school characteristics of interest, for each state, the central region, and the nation. All analyses of access will examine both student- and school-level access.

Projected Release Date: Spring 2021

Partnership or Research Alliance: Rural Education Research Alliance

Related Products: What's Happening?

Principal Investigators & Affiliation:
Douglas Gagnon, Marzano Research
Jing Liu, Marzano Research