2026 ASEE Annual Conference & Exposition

Analyzing Curriculum Structure and Student Navigation Using Graph Theory in Engineering Education

Presented at DSAI-Session 10: Curriculum Analytics, Degree Planning, and Student Pathways

In engineering education, curriculum design quietly structures every student’s journey. It shapes what knowledge they encounter, how they build expertise, and who ultimately succeeds. Yet, despite its centrality, curriculum often remains a static map rather than a system open to analysis and redesign. This work-in-progress paper proposes a network-based framework that reconceptualizes curriculum as a living, interconnected system shaped by relationships among courses, learning objectives, and digital resources.

Drawing on graph learning analytics and theories of curriculum design and networked learning, the framework models these relationships to reveal patterns of coherence, accessibility, and progression within engineering programs. It provides a mechanism for tracing how design choices influence learning pathways and for identifying points where structure may constrain or enable opportunity. Using artifacts such as syllabi, program maps, and digital learning environments, the framework integrates multiple layers of data to represent curriculum as both a pedagogical and analytical construct.

This work positions curriculum analysis as a dynamic and data-informed process for improving engineering education. The contribution lies not in reporting outcomes but in establishing a scalable, theoretically grounded approach for examining curricular systems. By reframing curriculum as an evolving network, this study opens new possibilities for designing equitable, coherent, and evidence-based learning pathways.

Authors
  1. Dr. Yeonji Jung Texas A&M University [biography]
  2. Dr. Sunay Palsole Texas A&M University [biography]
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