A Practical Computer Adaptive Testing Model for Small-Scale Scenarios

Computer adaptive testing (CAT) is theoretically sound and efficient, and is commonly seen in larger testing programs. It is, however, rarely seen in a smaller-scale scenario, such as in classrooms or business daily routines, because of the complexity of most adopted Item Response Theory (IRT) models. While the Sequential Probability Ratio Test (SPRT) model is less complicated, it only provides the examinee’s mastery result. We thus propose an SPRT-based adaptive testing approach that is simpler to implement while still being able to approximate IRT scores in semantic or rank levels for flexible assessment needs. An English adaptive testing prototype is implemented and benchmarked to the Test of English as a Foreign Language (TOEFL) testing results. Generally, this research empirically demonstrates the validity of the proposed SPRT-based testing approach as well as the technical feasibility for teachers and business organizations to really take advantage of CAT in their daily routines.