01950nas a2200121   4500008003900000245011400039210006900153300001200222490000700234520151600241100001801757856005301775       2016                          d00aMaximum Likelihood Score Estimation Method With Fences for Short-Length Tests and Computerized Adaptive Tests0 aMaximum Likelihood Score Estimation Method With Fences for Short  a289-3010 v403 aA critical shortcoming of the maximum likelihood estimation (MLE) method for test score estimation is that it does not work with certain response patterns, including ones consisting only of all 0s or all 1s. This can be problematic in the early stages of computerized adaptive testing (CAT) administration and for tests short in length. To overcome this challenge, test practitioners often set lower and upper bounds of theta estimation and truncate the score estimation to be one of those bounds when the log likelihood function fails to yield a peak due to responses consisting only of 0s or 1s. Even so, this MLE with truncation (MLET) method still cannot handle response patterns in which all harder items are correct and all easy items are incorrect. Bayesian-based estimation methods such as the modal a posteriori (MAP) method or the expected a posteriori (EAP) method can be viable alternatives to MLE. The MAP or EAP methods, however, are known to result in estimates biased toward the center of a prior distribution, resulting in a shrunken score scale. This study introduces an alternative approach to MLE, called MLE with fences (MLEF). In MLEF, several imaginary “fence” items with fixed responses are introduced to form a workable log likelihood function even with abnormal response patterns. The findings of this study suggest that, unlike MLET, the MLEF can handle any response patterns and, unlike both MAP and EAP, results in score estimates that do not cause shrinkage of the theta scale.1 aHan, Kyung, T  uhttp://apm.sagepub.com/content/40/4/289.abstract01492nas a2200121   4500008003900000245009200039210006900131300001200200490000700212520108000219100001801299856005301317       2013                          d00aItem Pocket Method to Allow Response Review and Change in Computerized Adaptive Testing0 aItem Pocket Method to Allow Response Review and Change in Comput  a259-2750 v373 a<p>Most computerized adaptive testing (CAT) programs do not allow test takers to review and change their responses because it could seriously deteriorate the efficiency of measurement and make tests vulnerable to manipulative test-taking strategies. Several modified testing methods have been developed that provide restricted review options while limiting the trade-off in CAT efficiency. The extent to which these methods provided test takers with options to review test items, however, still was quite limited. This study proposes the item pocket (IP) method, a new testing approach that allows test takers greater flexibility in changing their responses by eliminating restrictions that prevent them from moving across test sections to review their answers. A series of simulations were conducted to evaluate the robustness of the IP method against various manipulative test-taking strategies. Findings and implications of the study suggest that the IP method may be an effective solution for many CAT programs when the IP size and test time limit are properly set.</p>
1 aHan, Kyung, T  uhttp://apm.sagepub.com/content/37/4/259.abstract01355nas a2200133   4500008003900000022001400039245010100053210006900154300001400223490000700237520090400244100001801148856005501166       2012                          d  a1745-398400aAn Efficiency Balanced Information Criterion for Item Selection in Computerized Adaptive Testing0 aEfficiency Balanced Information Criterion for Item Selection in   a225–2460 v493 a<p>Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation and long-term quality control of CAT. This study proposed a new item selection method using the &ldquo;efficiency balanced information&rdquo; criterion to address issues with the maximum Fisher information method and stratification methods. According to the simulation results, the new efficiency balanced information method had desirable advantages over the other studied item selection methods in terms of improving the optimality of CAT assembly and utilizing items with low a-values while eliminating the need for item pool stratification.</p>
1 aHan, Kyung, T  uhttp://dx.doi.org/10.1111/j.1745-3984.2012.00173.x