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Autor/inn/en | Phan, Vinhthuy; Wright, Laura; Decent, Bridgette |
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Titel | Optimizing Financial Aid Allocation to Improve Access and Affordability to Higher Education |
Quelle | In: Journal of Educational Data Mining, 14 (2022) 3, S.26-51 (26 Seiten)
PDF als Volltext |
Zusatzinformation | ORCID (Phan, Vinhthuy) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
Schlagwörter | 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; Tennessee (Memphis) Finanzielle Beihilfe; Studienfinanzierung; Studienförderung; Education; Access; Bildung; Zugang; Bildungszugang; Leistungsvergütung; Künstliche Intelligenz; Hochschulzugang; Hochschulzulassung; Zulassung; Ressourcenallokation; University; Universität; College applications; Studienbewerber; Bildungsfonds; Finanzhaushalt; Einkommen; Charakterisierung; Profilanalyse; Auswertung |
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. (As Provided). |
Anmerkungen | International Educational Data Mining. e-mail: jedm.editor@gmail.com; Web site: https://jedm.educationaldatamining.org/index.php/JEDM |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |