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КыргызчаAdaptive Testing & Assessment for EdTech
IRT/CAT, banks of tasks, security, anti-cheat and fairness for accurate and personalized assessments.
Adaptive tests with IRT/CAT reduce the duration and improve the accuracy of assessing a student's level while maintaining security, transparency, and fairness.
Dynamic Task Selection from a Restricted Bank.
Recommendations for subsequent learning resources.
Anti-cheat: behavioral anomalies, proctors, cameras (policies).
Security Policies; Anti-Cheat Logs.
IRT calibration; CAT algorithm (MLE/EAP/Bayes).
Anti-cheat classifiers; anomalies.
Frequently asked questions
What does IRT calibration involve?
IRT calibration involves collecting sufficient data on student responses to tasks within the bank, allowing for a precise estimation of difficulty levels.
How is CAT logic implemented to determine task selection?
CAT logic is implemented using algorithms such as MLE (Maximum Likelihood Estimation), EAP (Item Response Theory), or Bayes' Theorem to dynamically adjust difficulty based on student performance.
What types of anti-cheat signals and policies are utilized in adaptive testing systems?
Anti-cheat signals include behavioral anomalies detected by the system, the presence of proctors observing students, and camera monitoring – all governed by strict privacy and user experience (UX) policies.
How do recommendations for learning resources integrate with adaptive test results?
Recommendations for subsequent learning resources are generated based on the student's performance during the adaptive assessment, often integrated seamlessly with Learning Management Systems (LMS).
▶ Try it live
Everything above runs in your browser — open Earthquake Wave Propagation Simulation and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.