Students' actions while working with a tuoring system were used to generate estimates of learning goals, specifically, the goal of learning by using multimedia help resources, and the goal of learning through independent problem solving. A Dynamic Bayesian Network (DBN) model was trained with interface action and inter-action interval latency data from 115 high school students, and then tested with action data from an independent sample of 135 students. Estimates of learning goals generated by the model predicted student performance on a post-test of math achievement, whereas pre-test performance did not.
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