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A Polytomous Computerized-Adaptive Testing that Rewards Partial Knowledge

Partial knowledge is one of the main factors to take into account when dealing with the improvement of administration of Multiple Choice Questions. Various strategies have been proposed for this factor in traditional testing environment. However, few researches were designed to investigate the impact of partial knowledge on computerized-adaptive testing (CAT). This study proposed a CAT which fits confidence-weighting scheme into graded response model (GRM). The results show the polytomous method is able to assess partial knowledge of examinees with fewer items and higher predictive validity. Besides, the estimated ability is not as likely to be affected by guessing and therefore more consisted with examinee's true ability.