A graph-theoretic framework for analyzing and designing chemical engineering curricula

Topics and courses that compose chemical engineering curricula are interconnected in a complex manner. The organization/structure of chemical engineering curricula closely matches the practice of breaking down chemical processes into fundamental phenomena (e.g., thermo, balances, and transport) and unit operations (e.g., reactors, separators, and heat exchangers). Emergence of modern topics (e.g., sustainability and molecular engineering) and advances in pedagogy call for the analysis and potential re-organization of curricula (e.g., use of case studies to foster integration of courses and include new topics/courses in a synergistic manner). In this work, we propose a graph-theoretic abstraction to represent, analyze, and reorganize the structure of curricula. In this abstraction, nodes represent topics/concepts, edges represent connectivity/dependencies between topics, and courses can be interpreted as collections of topics that are tightly interconnected (also known as clusters or modules). The abstraction enables the use of algorithms and software tools of graph theory and optimization to formalize the visualization and evaluation of curricula (e.g., identify key topics) and to identify re-organization strategies (e.g., defining strategic modules/courses that maximize topic cohesiveness/connectivity). Additionally, the abstraction can help formalize and facilitate discussions between instructors that might have different priorities/perspectives on curriculum content and organization. We provide case studies that analyze real curricula at the University of Wisconsin–Madison to highlight the benefits of the proposed framework.