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Optimizing Financial Aid Allocation to Improve Access and Affordability to Higher Education

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Title: Optimizing Financial Aid Allocation to Improve Access and Affordability to Higher Education
Language: English
Authors: Phan, Vinhthuy (ORCID 0000-0001-6108-1228), Wright, Laura, Decent, Bridgette
Source: Journal of Educational Data Mining. 2022 14(3):26-51.
Availability: International Educational Data Mining. e-mail: jedm.editor@gmail.com; Web site: https://jedm.educationaldatamining.org/index.php/JEDM
Peer Reviewed: Y
Page Count: 26
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Student Financial Aid, Access to Education, Merit Scholarships, Artificial Intelligence, College Admission, Resource Allocation, Universities, College Applicants, Financial Needs, Educational Finance, Paying for College, Budgets, Enrollment Trends, Income, Student Characteristics, Profiles, Data Analysis, Enrollment Management, Student Diversity
Geographic Terms: Tennessee (Memphis)
ISSN: 2157-2100
Abstract: The allocation of merit-based awards and need-based aid is important to both universities and students who wish to attend the universities. Current approaches tend to consider only institution-centric objectives (e.g. enrollment, revenue) and neglect student-centric objectives in their formulations of the problem. There is lack of consideration to the need to improve access and affordability to higher education. Previously, we contributed a metaheuristic and machine learning approach for optimizing strategies that allocate merit-based awards and need-based aid. The approach can be used to optimize both institutioncentric (e.g. enrollment and revenue) and student-centric objectives (affordability and accessibility to higher education). We now employed an improved version of this approach to explore comprehensively a recent admission dataset from our university. We showed that current applicants depended very much on financial sources other than federal and institution aid to attend the university. This potentially created a financial burden for many of these applicants. We identified seven budget-friendly strategies that promise to increase access to higher education significantly by more than 100%, while still keeping it affordable for students and limiting a budget increase to less than 7%. Additionally, we identified a total of 111 strategies, including those that benefit from more aggressive changes in the budget to obtain higher increases in enrollment, revenue, and/or higher affordability and accessibility for students. This method may be used by other institutions in ways that best fit their institutional objectives and students' profiles.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1373125
Database: ERIC
FullText Text:
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  Data: Optimizing Financial Aid Allocation to Improve Access and Affordability to Higher Education
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  Data: <searchLink fieldCode="AR" term="%22Phan%2C+Vinhthuy%22">Phan, Vinhthuy</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6108-1228">0000-0001-6108-1228</externalLink>)<br /><searchLink fieldCode="AR" term="%22Wright%2C+Laura%22">Wright, Laura</searchLink><br /><searchLink fieldCode="AR" term="%22Decent%2C+Bridgette%22">Decent, Bridgette</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Educational+Data+Mining%22"><i>Journal of Educational Data Mining</i></searchLink>. 2022 14(3):26-51.
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  Data: International Educational Data Mining. e-mail: jedm.editor@gmail.com; Web site: https://jedm.educationaldatamining.org/index.php/JEDM
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  Data: 26
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Student+Financial+Aid%22">Student Financial Aid</searchLink><br /><searchLink fieldCode="DE" term="%22Access+to+Education%22">Access to Education</searchLink><br /><searchLink fieldCode="DE" term="%22Merit+Scholarships%22">Merit Scholarships</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22College+Admission%22">College Admission</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+Allocation%22">Resource Allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Universities%22">Universities</searchLink><br /><searchLink fieldCode="DE" term="%22College+Applicants%22">College Applicants</searchLink><br /><searchLink fieldCode="DE" term="%22Financial+Needs%22">Financial Needs</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Finance%22">Educational Finance</searchLink><br /><searchLink fieldCode="DE" term="%22Paying+for+College%22">Paying for College</searchLink><br /><searchLink fieldCode="DE" term="%22Budgets%22">Budgets</searchLink><br /><searchLink fieldCode="DE" term="%22Enrollment+Trends%22">Enrollment Trends</searchLink><br /><searchLink fieldCode="DE" term="%22Income%22">Income</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Profiles%22">Profiles</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Enrollment+Management%22">Enrollment Management</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Diversity%22">Student Diversity</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Tennessee+%28Memphis%29%22">Tennessee (Memphis)</searchLink>
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  Data: 2157-2100
– Name: Abstract
  Label: Abstract
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  Data: The allocation of merit-based awards and need-based aid is important to both universities and students who wish to attend the universities. Current approaches tend to consider only institution-centric objectives (e.g. enrollment, revenue) and neglect student-centric objectives in their formulations of the problem. There is lack of consideration to the need to improve access and affordability to higher education. Previously, we contributed a metaheuristic and machine learning approach for optimizing strategies that allocate merit-based awards and need-based aid. The approach can be used to optimize both institutioncentric (e.g. enrollment and revenue) and student-centric objectives (affordability and accessibility to higher education). We now employed an improved version of this approach to explore comprehensively a recent admission dataset from our university. We showed that current applicants depended very much on financial sources other than federal and institution aid to attend the university. This potentially created a financial burden for many of these applicants. We identified seven budget-friendly strategies that promise to increase access to higher education significantly by more than 100%, while still keeping it affordable for students and limiting a budget increase to less than 7%. Additionally, we identified a total of 111 strategies, including those that benefit from more aggressive changes in the budget to obtain higher increases in enrollment, revenue, and/or higher affordability and accessibility for students. This method may be used by other institutions in ways that best fit their institutional objectives and students' profiles.
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RecordInfo BibRecord:
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 26
    Subjects:
      – SubjectFull: Student Financial Aid
        Type: general
      – SubjectFull: Access to Education
        Type: general
      – SubjectFull: Merit Scholarships
        Type: general
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: College Admission
        Type: general
      – SubjectFull: Resource Allocation
        Type: general
      – SubjectFull: Universities
        Type: general
      – SubjectFull: College Applicants
        Type: general
      – SubjectFull: Financial Needs
        Type: general
      – SubjectFull: Educational Finance
        Type: general
      – SubjectFull: Paying for College
        Type: general
      – SubjectFull: Budgets
        Type: general
      – SubjectFull: Enrollment Trends
        Type: general
      – SubjectFull: Income
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Profiles
        Type: general
      – SubjectFull: Data Analysis
        Type: general
      – SubjectFull: Enrollment Management
        Type: general
      – SubjectFull: Student Diversity
        Type: general
      – SubjectFull: Tennessee (Memphis)
        Type: general
    Titles:
      – TitleFull: Optimizing Financial Aid Allocation to Improve Access and Affordability to Higher Education
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              Y: 2022
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