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Saultz, Andrew; Yaluma, Christopher B. – Journal of School Choice, 2017
We analyze the geographical distribution of, and access to, charter schools in the state of Ohio. Using poverty and race data from the U.S. Census, as well as publicly available student achievement scores, we analyze the locational preferences of charter schools. We use Geographic Information System (GIS) to visual display charter school locations…
Descriptors: Demography, Access to Education, Equal Education, Geographic Distribution
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Bozick, Robert; Gonzalez, Gabriella; Engberg, John – Journal of Student Financial Aid, 2015
The Pittsburgh Promise is a scholarship program that provides $5,000 per year toward college tuition for public high school graduates in Pittsburgh, Pennsylvania who earned a 2.5 GPA and a 90% attendance record. This study used a difference-in-difference design to assess whether the introduction of the Promise scholarship program directly…
Descriptors: Merit Scholarships, College Bound Students, Enrollment Influences, Enrollment Management
Wheatley, Vicki Ann – ProQuest LLC, 2012
The relationship between components of the local school district report card, school district typology, and the outcome of public school tax levy requests were examined in this study. A correlation research design was used to measure the relationship between the independent variables (performance index, average yearly progress, value added,…
Descriptors: School Taxes, Correlation, School Statistics, Student Records
Wagner, Barbara Gail Allen – ProQuest LLC, 2012
One of the educational reform methods sanctioned under No Child Left Behind legislation is the development of charter schools (King, 2007). While many studies have focused on comparing the student academic achievement rates of charter schools to traditional public schools, little empirical research exists comparing student academic achievement…
Descriptors: Charter Schools, Comparative Education, Comparative Analysis, School Effectiveness
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Kim, JoHyun; Bragg, Debra D. – Career and Technical Education Research, 2008
Using Astin's I-E-O model, relationships among the input (I) variables of gender, high school percentile rank, Tech Prep participation, and high school course-taking; environmental (E) variables of academic, career and technical education (CTE), and total dual credit and articulated credit; and output (O) variables of college readiness and total…
Descriptors: Community Colleges, Regression (Statistics), Predictor Variables, Dual Enrollment