Engineering curricular analytics as complex systems: Introducing, modeling, and empirically testing the sociotechnical curricular complexity (STCC) framework

Abstract Background Engineering curricula are often treated as linear pipelines, yet they function as complex sociotechnical systems. Prior curricular analytics research has primarily focused on structural features such as prerequisite chains, which explain little about variation in outcomes and limit targeted curricular reform. Purpose This study introduces the Sociotechnical Curricular Complexity (STCC) framework, integrating three interdependent layers: curricular architecture (CA), learning‐experience quality (LEQ), and individual‐level (IL) factors. Using single‐institution data, we test whether this multidimensional approach predicts program outcomes more reliably than structural baseline metrics. Methodology/Approach We compiled institutional records, degree plans, and course evaluations from seven engineering and computer science programs ( n = 13,878). Using linear mixed‐effects models for Grade Point Average (GPA) and regression models for Time‐To‐Degree (TTD), we developed a composite scoring approach to quantify sociotechnical complexity. Findings/Conclusions For GPA, STCC‐based models explained 20% of variance through fixed effects and 58% through fixed and random effects, compared to near‐zero and 39% for the baseline; for TTD, they explained 22% versus <1%. The framework also showed that complexity is driven by different layers across programs—structural rigidity in some, learning quality and IL factors in others—rather than any single dimension. Implications Framing curricula as complex sociotechnical systems reframes research and practice in engineering education. Conceptually, it advances curricular analytics by linking complexity to systems‐design perspectives. Methodologically, it offers a transferable framework for quantifying complexity more holistically and for identifying specific leverage points for intervention to reduce unnecessary complexity, ultimately promoting equitable outcomes.