Bayesian Adaptive Testing

Bayesian Adaptive Testing is a method that personalizes assessments by using probabilities to estimate an individual's abilities or traits. As a test-taker answers questions, the system updates its belief about their skill level using Bayes' theorem, which combines prior knowledge with new data. It then selects the next question that best reduces uncertainty, making the test more efficient and accurate. This approach adapts in real-time, focusing on questions that provide the most informative insights about the individual’s abilities, leading to a tailored and streamlined assessment process.