IEEE Transactions on Education
Contribution: This article uses student semester grade point average (GPA) as a measure of student success to take into account the temporal effects in student success. The findings highlight the student performance based on their demographic status and use of university resources such as financial aid. College campuses should not only increase current resources but also raise awareness of current resources and make them more accessible (e.g., easier to apply or automatic applications). This is especially important for some demographics such as Hispanic first-generation students. Background: Higher education institutions are facing retention and graduation problems. One way to improve this is by understanding why students are not academically successful. Research Questions: In this study, demographic information and past academic records were analyzed to understand patterns of student success. Methodology: A cluster analysis was conducted to understand groups of students based on academic performance and demographic information. Examples of these factors are enrollment status, financial status, first-generation status, housing status, and transfer status. For the purpose of getting more accurate results, the students were separated into two different groups according to their admission status: 1) freshman and 2) transfer. Findings: The results indicate Hispanic, first-generation, low-income students are not likely to apply for financial aid although they are eligible. They have lower GPA and take fewer units per semester than other students. This can cause delayed graduation and accumulating more debt.
National Science Foundation
Clustering methods, data mining, engineering education, machine learning, student success
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Farshid Marbouti, Jale Ulas, and Ching Ho Wang. "Academic and Demographic Cluster Analysis of Engineering Student Success" IEEE Transactions on Education (2021): 261-266. https://doi.org/10.1109/TE.2020.3036824