Method and system for bayesian network-based standard or skill mastery determination using a collection of interim assessments

This invention describes a software system that uses a probabilistic model called a Bayesian network to figure out how well someone understands specific skills or topics. It works by giving them short tests, then analyzing their answers using a special 'Q-matrix' that links test questions to the skills being assessed. The system then calculates a probability score for their mastery of each skill. The claims narrow the invention to include a content library and a user-facing graphical Q-matrix.

Why it matters: Filed before the widespread adoption of advanced AI for personalized learning. Tools for implementing Bayesian networks and processing large educational datasets are significantly more mature and accessible now, making such adaptive assessment systems more feasible and performant.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, Bayesian network, Q-matrix, database

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