@article {2608,
	title = {The Information Product Methods: A Unified Approach to Dual-Purpose Computerized Adaptive Testing},
	journal = {Applied Psychological MeasurementApplied Psychological Measurement},
	volume = {42},
	year = {2017},
	month = {2018/06/01},
	pages = {321 - 324},
	abstract = {This 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.},
	isbn = {0146-6216},
	url = {https://doi.org/10.1177/0146621617730392},
	author = {Zheng, Chanjin and He, Guanrui and Gao, Chunlei}
}
@article {2506,
	title = {High-Efficiency Response Distribution{\textendash}Based Item Selection Algorithms for Short-Length Cognitive Diagnostic Computerized Adaptive Testing},
	journal = {Applied Psychological Measurement},
	volume = {40},
	number = {8},
	year = {2016},
	pages = {608-624},
	abstract = {Cognitive 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{\textendash}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.},
	doi = {10.1177/0146621616665196},
	url = {http://apm.sagepub.com/content/40/8/608.abstract},
	author = {Zheng, Chanjin and Chang, Hua-Hua}
}
@article {2349,
	title = {An Enhanced Approach to Combine Item Response Theory With Cognitive Diagnosis in Adaptive Testing},
	journal = {Journal of Educational Measurement},
	volume = {51},
	number = {4},
	year = {2014},
	pages = {358{\textendash}380},
	abstract = {<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>
},
	issn = {1745-3984},
	doi = {10.1111/jedm.12057},
	url = {http://dx.doi.org/10.1111/jedm.12057},
	author = {Wang, Chun and Zheng, Chanjin and Chang, Hua-Hua}
}
