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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorDimara, Evanthia
dc.contributor.authorDijk, Lars van
dc.date.accessioned2024-04-04T23:02:04Z
dc.date.available2024-04-04T23:02:04Z
dc.date.issued2024
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/46249
dc.description.abstractThis study has investigated the impact of data visualization on decision-making and financial self-efficacy in student loans. Interviews have revealed a simplistic decision-making process of students when taking out a student loan, primarily focusing on the present gains while neglecting the future consequences. Due to the multitude of factors influencing student loans and the inadequacy of current tools in illustrating the impact of each variable, a new data visualization tool called StudentViz has been created to assist students in making informed student loan decisions. StudentViz allows students to add various loan plans based on certain inputs and visually compare the important characteristics of each loan plan to gain a better understanding of the future consequences of loan decisions. An insight-based evaluation in combination with interviews has revealed that StudentViz supports the exploration of the effects of different factors, for example interest rates. Moreover, users of StudentViz scored high on financial self-efficacy indicating they believe they have the capacity to make informed student loan choices, but further research is necessary for definitive conclusions. All in all, StudentViz provides students with a deeper understanding of the repercussions of specific loan decisions, potentially empowering them to make more informed choices.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectData Visualization in Higher education Financing: Aiding Student Loan Decisions
dc.titleData Visualization in Higher education Financing: Aiding Student Loan Decisions
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsData visualization, student loans, loans, finance, tabular visualization
dc.subject.courseuuHuman-Computer Interaction
dc.thesis.id29744


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