We propose in this work a novel approach to retrieve the prerequisite structure of a domain model from learner traces. We introduce the E-PRISM framework that includes the causal effect of prerequisite relationships in the learner model for predicting the learner’s performance with knowledge tracing. By studying the distribution of the learned values of each learner model parameter from synthetic data, we propose new metrics for measuring the existence, direction, and strength of a prerequisite relationship. We apply the same methodology to real-world datasets and observe promising results in retrieving the prerequisite structure of a domain model from learner traces.