Method and system to adapt computer-based instruction based on heuristics

This invention describes a way to make computer-based lessons smarter. It works by assigning a 'teaching quality score' to a lesson. Before a student starts, the system predicts how well they'll do. After they complete the lesson, it checks their actual performance and then adjusts that 'teaching quality score' based on how well they did, and potentially how other students have performed. The claims specifically focus on adjusting this 'teaching quality score' rather than directly adapting the lesson content itself.

Why it matters: Filed before the widespread adoption of advanced machine learning and big data analytics, which can now significantly enhance the 'performance heuristics' and 'Effectiveness Factor' by learning from vast amounts of student data. Modern AI can build and refine these adaptive learning models with far greater sophistication and scale than was practical in 2008.

Status: ExpiredProtection ended and was never renewed
How hard to build: ModerateSoftware logic, data processing, machine learning

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