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This invention describes a computer system that automatically figures out what a student understands. It works by first organizing all the learning topics into a structured map, then tracking everything a student does with learning materials tagged with those topics. Using this activity data, it builds a statistical model to estimate how well the student grasps different concepts, specifically detailing how this model uses both directly observed student actions and inferred underlying knowledge.
Why it matters: Filed before widespread adoption of cloud computing and accessible machine learning frameworks. Today, processing vast student interaction logs and building complex Bayesian networks is far more feasible and cost-effective.
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