The critical revision of the content, scope and alignment of curricula is essential for improving students success at Higher-Ed institutions. The effort is never trivial, as students are accepted from multiple sources (e.g. high schools, community colleges, other institutions) with different academic preparation, socioeconomic background, and motivation. In addition, students follow diverse paths either according to their interests, or according to the necessities, such as academic or financial requirements. Some graduate from their entry majors in 4 years, some need more time, some transfer to different disciplines, and some leave their universities. Accordingly, providing Higher-Ed decision makers with an accurate summary of these diverse student characteristics is a necessity to help them make better data-informed decisions for improving students success. In this regard, any data mining methodology that can convey valuable patterns from student data sets in clear and informative fashion will be valuable. In this study, we discuss the development and use of such a visual tool based on the Sankey Diagram. It presents students progress and mobility patterns in an easily understandable format, was developed using open source software, and was used by several departments of a research intensive Higher-Ed institution of more than thirty-thousand students during their academic review process. This paper provides a general discussion about how these visuals could be used in Higher-Ed institutions by discussing problems that can be addressed, detailing the data needs, the development methods, comparisons with other reporting methods, and how they were used in actual practice.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Oran, Ali; Martin, Andrew; Klymkowsky, Michael; and Stubbs, Robert, "Identifying Students' Progress and Mobility Patterns in Higher Education Through Open-Source Visualization" (2019). University Administration Faculty and Staff Contributions. 1.