Abstract
Reviewing academic curricula requires a significant investment of time and expertise. Beyond accreditation, curriculum may be reviewed in part or in whole during other administrative efforts including the consideration of new elective courses, faculty-student advising, admission of transfer students, internal audits, and more. These activities often require multiple people with deep knowledge of the coursework as well as the discipline(s) involved to pour over scattered documentation and comparatively limited assessment data in order to make an informed decision. In this work, we explored the development of a semi-automated computational approach to visualize a curriculum as described in official course listings at a topic level of detail. We show how our approach can help provide a detailed view of how topics are covered across multiple courses and how these visualizations can show similarities and differences for individual student registration records, paving the way for personalized student support. We also identified opportunities for improvement in this method, including the need to develop more robust topic mapping techniques for short texts.
Original language | English (US) |
---|---|
Article number | 614 |
Journal | Education Sciences |
Volume | 15 |
Issue number | 5 |
DOIs | |
State | Published - May 2025 |
Keywords
- computer science
- curriculum visualization
- higher education
- natural language processing (NLP)
- student outcomes
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Education
- Physical Therapy, Sports Therapy and Rehabilitation
- Developmental and Educational Psychology
- Public Administration
- Computer Science Applications