A scoping review of methods used to analyze engineering curricula quantitatively with curricular analytics

This paper examines how engineering education scholars have employed quantitative metrics to analyze curricula. This work is situated within curricular analytics, an approach that employs network analysis to measure "curricular complexity" and its associations with outcomes, including retention and program quality. Since the introduction of this framework, researchers have proposed additional metrics to capture different dimensions of complexity. However, no effort has been made to consolidate these metrics in a single resource that highlights the suite of analytical options available to the community. To address this gap, we conducted a scoping review, beginning with foundational articles on curricular analytics and purposefully sampling papers that cited these works. Our guiding research question was: What metrics do researchers use to quantify the complexity of curricula? Of the 174 papers identified, 65 met our inclusion criteria after duplicates were removed. Through these studies, we identified 23 unique metrics, which we classified into structural and instructional complexity across three levels of analysis. We aim for this catalog of metrics to serve as a reference for the basics of curricular analytic metrics and as a practical tool to support curriculum design and optimization.