A student’s choice of higher education institution has enduring consequences extending beyond academics, affecting career trajectories and economic outcomes. Yet this decision is made under substantial uncertainty, arising from imperfect signals, information asymmetries, heterogeneous quality indicators, proliferating programs, and evolving employer demands. Uncertainty over whether post-program outcomes will meet pre-enrollment expectations further complicates the choice. Existing research is largely siloed into choice, perception, and realization studies, rarely tracing the lifecycle from expectations to outcomes and leaving a persistent choice-perception-realization gap. We propose a method to unify these literatures within a Choice-Perception-Realization (CPR) framework and operationalize it into an Integrated Choice and Latent Variable (ICLV) model by embedding latent constructs from the Theory of Planned Behavior and the Signaling Theory within a random utility, discrete choice framework, and linking them through Rational Choice Theory with Bayesian updating to post-enrollment and early career realization. As a proof-of-concept, we provide a complete R implementation using synthetic data and an end-to-end workflow demonstrating the model’s capacity to handle complex interactions among student identity, institutional signals, and heterogeneous preferences. We extend the model into a dynamic longitudinal framework with feedback loops and illustrate its compatibility with causal inference techniques. Through detailed case studies, we showcase the model’s strategic utility for institutional decision-making. The framework illustrates how placement-centric signals, perceived value, social norms, and feasibility jointly drive choice, and how expectation-realization alignment underpins post-enrollment satisfaction. It also identifies the strategic trade-off between aggressive signaling and long-run reputation.
Karn et al. (Fri,) studied this question.