Survey of Computerized Adaptive Testing: A Machine Learning Perspective

Understand

Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual performance.

• Compared to traditional, non-personalized testing methods, CAT requires fewer questions and provides more accurate assessments.
• As a result, CAT has been widely adopted across various fields, including education, healthcare, sports, sociology, and the evaluation of AI models.
• While traditional methods rely on psychometrics and statistics, the increasing complexity of large-scale testing has spurred the integration of machine learning techniques.