01106nas a2200169   4500008003900000020001400039245010200053210006900155260001500224300001400239490000700253520057900260100001900839700001600858700001700874856004500891       2017                          d  a0146-621600aThe Information Product Methods: A Unified Approach to Dual-Purpose Computerized Adaptive Testing0 aInformation Product Methods A Unified Approach to DualPurpose Co  c2018/06/01  a321 - 3240 v423 aThis article gives a brief summary of major approaches in dual-purpose computerized adaptive testing (CAT) in which the test is tailored interactively to both an examinee?s overall ability level, ?, and attribute mastery level, α. It also proposes an information product approach whose connections to the current methods are revealed. An updated comprehensive empirical study demonstrated that the information product approach not only can offer a unified framework to connect all other approaches but also can mitigate the weighting issue in the dual-information approach.1 aZheng, Chanjin1 aHe, Guanrui1 aGao, Chunlei  uhttps://doi.org/10.1177/014662161773039202164nas a2200133   4500008003900000245014400039210007100183300001200254490000700266520166600273100001901939700001901958856005301977       2016                          d00aHigh-Efficiency Response Distribution–Based Item Selection Algorithms for Short-Length Cognitive Diagnostic Computerized Adaptive Testing0 aHighEfficiency Response Distribution–Based Item Selection Algori  a608-6240 v403 aCognitive diagnostic computerized adaptive testing (CD-CAT) purports to obtain useful diagnostic information with great efficiency brought by CAT technology. Most of the existing CD-CAT item selection algorithms are evaluated when test length is fixed and relatively long, but some applications of CD-CAT, such as in interim assessment, require to obtain the cognitive pattern with a short test. The mutual information (MI) algorithm proposed by Wang is the first endeavor to accommodate this need. To reduce the computational burden, Wang provided a simplified scheme, but at the price of scale/sign change in the original index. As a result, it is very difficult to combine it with some popular constraint management methods. The current study proposes two high-efficiency algorithms, posterior-weighted cognitive diagnostic model (CDM) discrimination index (PWCDI) and posterior-weighted attribute-level CDM discrimination index (PWACDI), by modifying the CDM discrimination index. They can be considered as an extension of the Kullback–Leibler (KL) and posterior-weighted KL (PWKL) methods. A pre-calculation strategy has also been developed to address the computational issue. Simulation studies indicate that the newly developed methods can produce results comparable with or better than the MI and PWKL in both short and long tests. The other major advantage is that the computational issue has been addressed more elegantly than MI. PWCDI and PWACDI can run as fast as PWKL. More importantly, they do not suffer from the problem of scale/sign change as MI and, thus, can be used with constraint management methods together in a straightforward manner.1 aZheng, Chanjin1 aChang, Hua-Hua  uhttp://apm.sagepub.com/content/40/8/608.abstract01835nas a2200157   4500008003900000022001400039245010200053210006900155300001400224490000700238520133800245100001501583700001901598700001901617856004101636       2014                          d  a1745-398400aAn Enhanced Approach to Combine Item Response Theory With Cognitive Diagnosis in Adaptive Testing0 aEnhanced Approach to Combine Item Response Theory With Cognitive  a358–3800 v513 a<p>
	Computerized adaptive testing offers the possibility of gaining information on both the overall ability and cognitive profile in a single assessment administration. Some algorithms aiming for these dual purposes have been proposed, including the shadow test approach, the dual information method (DIM), and the constraint weighted method. The current study proposed two new methods, aggregate ranked information index (ARI) and aggregate standardized information index (ASI), which appropriately addressed the noncompatibility issue inherent in the original DIM method. More flexible weighting schemes that put different emphasis on information about general ability (i.e., &theta; in item response theory) and information about cognitive profile (i.e., &alpha; in cognitive diagnostic modeling) were also explored. Two simulation studies were carried out to investigate the effectiveness of the new methods and weighting schemes. Results showed that the new methods with the flexible weighting schemes could produce more accurate estimation of both overall ability and cognitive profile than the original DIM. Among them, the ASI with both empirical and theoretical weights is recommended, and attribute-level weighting scheme is preferred if some attributes are considered more important from a substantive perspective.</p>
1 aWang, Chun1 aZheng, Chanjin1 aChang, Hua-Hua  uhttp://dx.doi.org/10.1111/jedm.12057