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Using R Shiny to develop a dashboard using IPEDS, U.S. Census, and bureau of labor statistics data
Mark A Perkins1, Jonathan W Carrier1
1College of Education, University of Wyoming, Laramie, Wyoming, United States of America.
Plos One
|January 11, 2023
Summary
This study created a dashboard using US education, census, and labor data to explore higher education institutions, enrollment, and career outcomes. It links degrees to job projections and wages, aiding informed decision-making.
Area of Science:
- Educational Data Analysis
- Higher Education Research
- Data Visualization
Background:
- The Integrated Postsecondary Educational Data System (IPEDS) collects extensive data on US higher education institutions.
- Accessing and integrating data from IPEDS, the US Census Bureau, and the Bureau of Labor Statistics presents challenges for users.
- A need exists for a user-friendly tool to explore institutional, community, and career-related information.
Purpose of the Study:
- To develop an interactive RStudio (Posit) dashboard for exploring US higher education data.
- To integrate data from IPEDS, the US Census Bureau, and the Bureau of Labor Statistics into a single platform.
- To provide users with tools for analyzing institutional characteristics, enrollment trends, student outcomes, and career pathways.
Main Methods:
- Development of an RStudio dashboard utilizing R programming language.
- Integration of data from the Integrated Postsecondary Educational Data System (IPEDS).
- Incorporation of data from the United States Census Bureau and the Bureau of Labor Statistics.
Main Results:
- A functional dashboard providing comprehensive information on US higher education institutions.
- Capabilities for users to explore enrollment data, demographics, and institutional outcomes.
- Features enabling correlation of community variables with institutional data and linking degrees to career projections and wages.
Conclusions:
- The developed dashboard offers a valuable resource for stakeholders interested in US higher education.
- The tool facilitates data-driven exploration of institutional performance, student success, and workforce alignment.
- The R programming language provides a robust framework for creating such integrated data analysis tools.
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