Understanding Undergraduates' Perceptions of Student Debt Visualizations: A Human-Centered Approach
Open Access
- Author:
- Hubbard, Glenn
- Area of Honors:
- Data Sciences
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Syed M. Billah, Thesis Supervisor
John Yen, Thesis Honors Advisor - Keywords:
- Data Science
Visualization
Debt
Student Debt
Human-Computer Interaction
HCI
DS
CS
Python
Excel
Psychology
Interpretivist
Grounded Theory
Undergraduate
Study
Human-Centered
Finance
Amortization
Chart
Graph
Line Graph
Bar Graph
Stacked Bar Graph
Plotly
Mortgage
Debt Crisis
Design - Abstract:
- Data Science, as a field, relies heavily on the translation of analytic results into visualizations to aid in the explainability of these results. Visualizations, such as graphs and infographics, serve as a tool to quickly interpret quantifiable results, however the design of these elements is often performed without a proper assessment of the data interpretation abilities of the target audience. Moreover, without consulting a particular audience, the effectiveness of one’s visualization can be lost within this audience, since everyone’s background may impact their understanding differently. This paper focuses on the design elements that work towards the creation of effective and broadly understandable data visualizations that relate to student debt. Student debt is of particular interest as this form of debt if applicable to millions within the United States. Student debt has been labeled as a financial burden that impacts home ownership and financial stability, which can have a cascading effect for the rest of the U.S. economy. While efforts are being made within the Biden Administration to cancel a portion of the U.S.’s student debt burden, these efforts are currently being held back in the Federal Court System. With no relief in sight, learning ways for individuals to best tackle and understand the impact of their debt burden is of critical importance for personal and societal financial stability. Through an interview-based IRB-approved study of Penn State University – University Park undergraduates, this paper will explore the aspects of effective debt visualizations and how one’s background impacts their understanding of both student debt and data visualization interpretations. Finally, design guidelines for stakeholders in the student debt industry will be presented for the assistance in the creation of future visualizations.