CAT

Computerized Adaptive Testing (CAT) is an assessment approach that dynamically adjusts question difficulty based on a candidate’s real-time performance. By selecting items aligned to the examinee’s estimated ability, CAT achieves high measurement precision with fewer questions while preserving blueprint balance, fairness, and efficiency.

AI-Enhanced CAT extends this adaptive measurement model by applying artificial intelligence to post-test analysis. The system evaluates response accuracy, difficulty levels, response time, and ability progression to develop a comprehensive understanding of the candidate’s performance profile.

Rather than ending with a score or pass–fail decision, AI-enhanced CAT generates a structured remediation plan tailored to the individual candidate. This plan identifies priority learning gaps, highlights strengths, and recommends targeted difficulty ranges and study strategies.

Through this integration, assessment becomes a continuous learning cycle. CAT provides precise measurement, while AI-driven remediation transforms assessment data into actionable guidance, supporting focused improvement and sustained competency development.