Information Technologies for Learning Principles of Fault-Tolerant Systems

Abstract

In this chapter, the authors present a methodology for developing a model-tracing cognitive tutor. The methodology is based on Bayesian probabilistic networks for generating pedagogical interventions. The presented probabilistic model increases fidelity assessment due to its ability of independently diagnosing the degree of mastery for every knowledge component involved in students' actions; fidelity assessment in education is the ability to represent students' cognitive states as close as possible for analysis and evaluation. The cognitive tutor was developed to promote a self-regulated learning approach with an open learner model. The open learner model let students change the learning flow by changing the assigned tasks. The authors explain in detail the structural construction and employed algorithms for developing a model-tracing cognitive tutor in the domain of fault-tolerant systems. Preliminary results and future work are also discussed to assess effectiveness of the proposed approach and its implication in actual educational programs.