Analyzing Curricular Pattern Complexity Using AI to Improve On-Time Graduation Rates
The rise of Artificial Intelligence (AI) enables automatic analysis of large amounts of data. Previously time-consuming and labor-intensive tasks can be completed much more efficiently with the use of AI. This work uses AI techniques to analyze and revise curricular patterns in an undergraduate degree for Software Engineering. Curricula often have long sequences where failure to pass a class within the sequence may jeopardize completion of the degree within four years. Manual analysis and revision of curricula by university faculty is a lengthy and labor-intensive process, causing changes to occur rarely and making it impossible to keep up with the changing needs of students. This work re...
| Authors | Lynn Vonderhaar, Juan Couder, Siri Siqveland et al. |
|---|---|
| Primary category | cs.CY |
| Published | 14 July 2026 |
| Last updated at source | 14 July 2026 |
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