Enhancing the program quality and college-level success metrics of an IT program at a large public university

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Abstract

Student success is a widely discussed and studied topic in higher education. Colleges and universities have been using college-level success metrics (time to degree, graduation, and retention rates) to measure student success. There are multiple factors that affect student success. Our previous study found that non-accredited Information Technology (IT) program within the Department of Computer Science and the way IT and Computer Science (CS) programs were established within the department and the resulting social comparisons were one among many factors that had a negative consequence on IT students' success. However, the IT program at the targeted university received accreditation from the Accreditation Board for Engineering and Technology (ABET) in 2013, and since then, many changes were made in the program. In this paper, we examine student data from IT undergraduate program at a large public university to identify who started the program in Spring 2014 and Fall 2014 semesters and dropped out, changed their major or successfully completed the program by Fall 2017. We also conducted a network analysis of the IT program curriculum to determine courses that were causing difficulty for students to continue in the program. Our results suggest that there is no significant improvement in college-level student success metrics since ABET accreditation. We conclude that IT programs in higher education institutions need to take additional program improvement measures that are student-centered to improve students' course passing rate. Based on our analyses, we propose necessary measures to improve both college-level success metrics and program quality.

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APA

Basavaraj, P., & Garibay, I. (2019). Enhancing the program quality and college-level success metrics of an IT program at a large public university. In SIGITE 2019 - Proceedings of the 20th Annual Conference on Information Technology Education (pp. 16–21). Association for Computing Machinery, Inc. https://doi.org/10.1145/3349266.3351418

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