Student Trajectories in Higher Education: Curriculum Structure, Causal Inference, and Simulation for Policy Design

By Hugo Roger Paz

Student trajectories are shaped by more than individual performance. They also emerge from the structures, rules, and constraints through which students must progress.
Student Trajectories in Higher Education develops a curriculum-aware framework for analysing student progression through the combined lenses of structural analysis, causal inference, and policy simulation.
The book introduces CAPIRE - the Curriculum-Aware Pipeline for Institutional Research and Education - an integrated analytical architecture built around five components: leakage-aware data design, curriculum graph modelling, trajectory heterogeneity, causal analysis, and agent-based simulation.
Rather than treating the curriculum as background context, the framework represents it as a structured network of prerequisites and progression constraints. This makes it possible to examine how bottlenecks, blocked pathways, accumulated delay, institutional rules, and contextual disturbances interact with heterogeneous student trajectories.
The empirical application draws on longitudinal data from a Civil Engineering programme at the National University of Tucum n, Argentina. The case is used to demonstrate how the framework can be implemented on real institutional data; its empirical findings are not presented as universal. The analytical architecture is intended to be transferable to other higher-education settings through appropriate local calibration.
The book addresses leakage-aware longitudinal data architecture, curriculum modelling through directed graphs, structural indicators of progression and curricular friction, trajectory heterogeneity, causal inference, agent-based simulation of policy scenarios, and institutional decision support.
Written as a rigorous academic monograph, the book is intended for researchers, institutional analysts, academic leaders, and professionals working in higher education analytics, engineering education, curriculum analysis, educational data mining, and evidence-informed policy design.

• Format: Paperback
• Language: English
• ISBN: B0HDLVSJ9Y
• ISBN13: 9798191725727
• Release Date: August 2026
• Publisher: Independently Published
• Length: 270 Pages
• Weight: 1.04 lbs.
• Dimensions: 0.6" x 7.0" x 10.0"