Transfer Student Success in Computer Science

This project applies computer science methods to human-centered datasets, with the goal of further understand the experiences of transfer students and how best to support them in computing education. This project is primarily led by Nawar Wali. Her academic and research interests lie at the intersection of computer science education, machine learning, knowledge graphs, and temporal data analysis, with a particular emphasis on transfer student success and equity in CS.

In March 2025, we presented a poster at the 2025 ACM Capital Region Celebration of Women in Computing (CAPWIC) titled “Machine Learning Insights into Academic Success in CS3: The Role of Mathematics and CS Coursework” (Wali & Hooshangi, 2025).

In July 2025, we published a paper at 2025 ACM ITiCSE Conference at Radboud University, Netherlands, titled “Transfer Students in Computer Science: Examining Barriers, Success Metrics, and Research Gaps” (Wali & Hooshangi, 2025).

The authors of the poster standing in front of the poster at a conference.

Nawar Wali presenting at the 2025 ACM ITiCSE Conference at Radboud University, Netherlands.

Future work on this project will be presented at the ACM Conference on International Computing Education Research (ICER) 2025 as part of the Doctoral Consortium.

References

2025

Machine Learning Insights into Academic Success in CS3: The Role of Mathematics and CS Coursework

Nawar Wali and Sara Hooshangi

In 2025 ACM Capital Region Celebration of Women in Computing (CAPWIC), Washington, DC, Mar 2025

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This research paper aims to understand how mathematics and computer science education influence the academic trajectory and performance of students in Computer Science degree programs, with a particular focus on CS3. By analyzing data from 3905 students over a decade at an R1 institution, this study examines course terms, grades, course completion, and program participation for all Computer Science and Math courses. Through extensive statistical and machine learning analysis on this comprehensive dataset, we investigate the correlation between students’ performance in mathematics and previous CS courses and their grades in the upper-level CS course, CS3. This study provides a nuanced understanding of the factors contributing to student success in advanced Computer Science coursework.
Transfer Students in Computer Science: Examining Barriers, Success Metrics, and Research Gaps

Nawar Wali and Sara Hooshangi

In Proceedings of the 30th ACM Conference on Innovation and Technology in Computer Science Education V. 1, Nijmegen, Netherlands, Jul 2025

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Transfer students play an important role in enhancing diversity within computer science programs. As first-generation college students, minorities, rural residents, and individuals from low-income backgrounds, transfer students represent a demographic critical to fostering innovation and inclusion in the field. However, while significant research has been conducted on transfer students in STEM disciplines, studies specifically addressing their experiences in computer science remain limited. This paper presents a preliminary systematic review of the literature to explore the challenges, successes, and gaps in the support of transfer students in computer science.