scholarly journals Closing the Gap: The Effect of a Targeted, Tuition-Free Promise on College Choices of High-Achieving, Low-Income Students

2018 ◽  
Author(s):  
Susan Dynarski ◽  
C.J. Libassi ◽  
Katherine Michelmore ◽  
Stephanie Owen
Keyword(s):  
Low Income ◽  
Low Income Students ◽  
College Choices ◽  
Closing The Gap ◽  
High Achieving

High-achieving, low-income students’ perspectives of how schools can promote the academic achievement of students living in poverty

2018 ◽  
Vol 22 (3) ◽  
pp. 224-236 ◽  
Author(s):  
Joseph M Williams ◽  
Arie T Greenleaf ◽  
Erin F Barnes ◽  
Tracey R Scott
Keyword(s):  
Academic Achievement ◽  
Middle School Students ◽  
Low Income ◽  
National Sample ◽  
Low Income Students ◽  
School Students ◽  
Public School Students ◽  
Relational Networks ◽  
High Achieving ◽  
Low Income Families

Children and adolescents from low-income families now comprise a majority of public school students nationally. As the number of students from low-income backgrounds increases, so does the achievement gap between them and their wealthier peers. This phenomenological qualitative study examined a national sample of high-achieving, low-income middle school students’ ( N = 24) perspectives on what schools can do to promote the academic achievement of students from low-income backgrounds. Three main themes and seven subthemes were identified: create a culture of hope, develop relational networks, and establish meaningful parent–school collaborations. Implications for counselors and educators serving youth living in poverty are discussed.

Closing the Gap: The Effect of Reducing Complexity and Uncertainty in College Pricing on the Choices of Low-Income Students

2021 ◽  
Vol 111 (6) ◽  
pp. 1721-1756
Author(s):  
Susan Dynarski ◽  
CJ Libassi ◽  
Katherine Michelmore ◽  
Stephanie Owen
Keyword(s):  
Low Income ◽  
Loss Aversion ◽  
Large Scale ◽  
Low Income Students ◽  
Present Bias ◽  
Selective Colleges ◽  
Enrollment Rates ◽  
Closing The Gap ◽  
Flagship University ◽  
Scale Experiment

High-achieving, low-income students attend selective colleges at far lower rates than upper-income students with similar achievement. Behavioral biases, intensified by complexity and uncertainty in the admissions and aid process, may explain this gap. In a large-scale experiment we test an early commitment of free tuition at a flagship university. The intervention did not increase aid: rather, students were guaranteed before application the same grant aid that they would qualify for in expectation if admitted. The offer substantially increased application (68 percent versus 26 percent) and enrollment rates (27 percent versus 12 percent). The results suggest that uncertainty, present bias, and loss aversion loom large in students’ college decisions. (JEL I22, I23, I24, D31, I28)

The Sequential College Application Process

2018 ◽  
Vol 13 (4) ◽  
pp. 545-575 ◽  
Author(s):  
Jonathan Smith
Keyword(s):  
Graduation Rates ◽  
Low Income ◽  
Low Income Students ◽  
Application Process ◽  
College Application ◽  
High Achieving ◽  
Sequential Nature ◽  
Exact Timing ◽  
College Characteristics

To demonstrate the sequential nature of the college application process, in this paper I analyze the evolution of applications among high-achieving low-income students through data on the exact timing of SAT score sends. I describe at what point students send scores to colleges and which score sends ultimately become applications, resulting in three main points. First, score sends are not synonymous with applications—rather, only 62 percent of score sends in this sample turn into applications. Second, the conversion from score send to application is nonrandom as it relates to college characteristics: Score sends are more likely to convert into applications when they are to colleges with lower tuition, higher graduation rates, and relatively near a student's home. Third, the timing of score sends is related to the probability of its becoming an application, whereby score sends sent relatively early are least likely to become applications. These facts imply that there is room for improvement when modeling the application process and, in addition, the timing of an intervention or policy may be critical to its success.

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