Constructing Shadow Tests in Variable-Length Adaptive Testing

摘要

Imposing content constraints is very important in most operational computerized adaptive testing (CAT) programs in educational measurement. Shadow test approach to CAT (Shadow CAT) offers an elegant solution to imposing statistical and nonstatistical constraints by projecting future consequences of item selection. The original form of Shadow CAT presumes fixed test lengths. The goal of the current study was to extend Shadow CAT to tests under variable-length termination conditions and evaluate its performance relative to other content balancing approaches. The study demonstrated the feasibility of constructing Shadow CAT with variable test lengths and in operational CAT programs. The results indicated the superiority of the approach compared with other content balancing methods.