College affordability is the ability to pay for all the costs necessary to attend college. It is one of the leading reasons for low-income high school students in the United States to not pursue or complete their education. This makes it a subject concerning not only to students, but also policymakers, and higher education institutions.
The College Affordability Model is a tool built by a team here at the University of Washington, to explore and improve the understanding of college affordability, and the role that various financing elements play for the students and their families. The data behind the model has been obtained from various sources including: Integrated Postsecondary Education Data System (IPEDS), United States Census Bureau, United States Department of Labor, Federal Register, State Higher Education Executive Officers (SHEEO) Association, Federal Student Aid Office and Office for Assistant Secretary for Planning and Evaluation (ASPE).
While the existing model has been successful in providing insights for policymakers, there are two major limitations with the current system architecture. First, with the focus always on the rapid fulfilment of functionality, the current architecture of the model has evolved gradually and is not easily modifiable. It’s difficult to add a new data source to the model without in-depth knowledge of the entire system. Second, recent developments have begun to expose APIs to many data sources for remote accessing. The current architecture doesn’t support this remote API access of data sources.
This project analyzes the limitations of the existing College Affordability model, surveys related work in the field, adopts relevant results in deriving a new architecture, and implements the new architecture and demonstrates its effectiveness. The new system divides the College Affordability Model into independent and configurable computation modules, where each module consists of a data source, logic filters and a result sink. As an integrated result of the new system, sample templates are provided to facilitate the integration of additional modules. The project identifies an effective target architecture that is modifiable and extensible, and demonstrates the validity of this target architecture by porting over the existing system.