@article {2754, title = {How Do Trait Change Patterns Affect the Performance of Adaptive Measurement of Change?}, journal = {Journal of Computerized Adaptive Testing}, volume = {10}, year = {2023}, pages = {32-58}, keywords = {adaptive measurement of change, computerized adaptive testing, longitudinal measurement, trait change patterns}, doi = {10.7333/2307-1003032}, author = {Ming Him Tai and Allison W. Cooperman and Joseph N. DeWeese and David J. Weiss} } @article {2702, title = {How Adaptive Is an Adaptive Test: Are All Adaptive Tests Adaptive?}, journal = {Journal of Computerized Adaptive Testing}, volume = {7}, year = {2019}, pages = {1-14}, keywords = {computerized adaptive test, multistage test, statistical indicators of amount of adaptation}, doi = {10.7333/1902-0701001}, url = {http://iacat.org/jcat/index.php/jcat/article/view/69/34}, author = {Mark Reckase and Unhee Ju and Sewon Kim} } @article {2692, title = {A Hybrid Strategy to Construct Multistage Adaptive Tests}, journal = {Applied Psychological Measurement}, volume = {42}, number = {8}, year = {2018}, pages = {630-643}, abstract = {How to effectively construct multistage adaptive test (MST) panels is a topic that has spurred recent advances. The most commonly used approaches for MST assembly use one of two strategies: bottom-up and top-down. The bottom-up approach splits the whole test into several modules, and each module is built first, then all modules are compiled to obtain the whole test, while the top-down approach follows the opposite direction. Both methods have their pros and cons, and sometimes neither is convenient for practitioners. This study provides an innovative hybrid strategy to build optimal MST panels efficiently most of the time. Empirical data and results by using this strategy will be provided.}, doi = {10.1177/0146621618762739}, url = {https://doi.org/10.1177/0146621618762739}, author = {Xinhui Xiong} } @article {2519, title = {Heuristic Constraint Management Methods in Multidimensional Adaptive Testing}, journal = {Educational and Psychological Measurement}, volume = {77}, number = {2}, year = {2017}, pages = {241-262}, abstract = {Although multidimensional adaptive testing (MAT) has been proven to be highly advantageous with regard to measurement efficiency when several highly correlated dimensions are measured, there are few operational assessments that use MAT. This may be due to issues of constraint management, which is more complex in MAT than it is in unidimensional adaptive testing. Very few studies have examined the performance of existing constraint management methods (CMMs) in MAT. The present article focuses on the effectiveness of two promising heuristic CMMs in MAT for varying levels of imposed constraints and for various correlations between the measured dimensions. Through a simulation study, the multidimensional maximum priority index (MMPI) and multidimensional weighted penalty model (MWPM), as an extension of the weighted penalty model, are examined with regard to measurement precision and constraint violations. The results show that both CMMs are capable of addressing complex constraints in MAT. However, measurement precision losses were found to differ between the MMPI and MWPM. While the MMPI appears to be more suitable for use in assessment situations involving few to a moderate number of constraints, the MWPM should be used when numerous constraints are involved.}, doi = {10.1177/0013164416643744}, url = {http://dx.doi.org/10.1177/0013164416643744}, author = {Sebastian Born and Andreas Frey} } @conference {2627, title = {How Adaptive is an Adaptive Test: Are all Adaptive Tests Adaptive?}, booktitle = {2017 IACAT Conference}, year = {2017}, month = {08/2017}, publisher = {Niigata Seiryo University}, organization = {Niigata Seiryo University}, address = {Niigata, Japan}, abstract = {

There are many different kinds of adaptive tests but they all have the characteristic that some feature of the test is customized to the purpose of the test. In the time allotted, it is impossible to consider the adaptation of all of this types so this address will focus on the \“classic\” adaptive test that matches the difficulty of the test to the capabilities of the person being tested. This address will first present information on the maximum level of adaptation that can occur and then compare the amount of adaptation that typically occurs on an operational adaptive test to the maximum level of adaptation. An index is proposed to summarize the amount of adaptation and it is argued that this type of index should be reported for operational adaptive tests to show the amount of adaptation that typically occurs.

Click for Presentation Video\ 

}, keywords = {Adaptive Testing, CAT}, url = {https://drive.google.com/open?id=1Nj-zDCKk3DvHA4Jlp1qkb2XovmHeQfxu}, author = {Mark D Reckase} } @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 {2462, title = {Hybrid Computerized Adaptive Testing: From Group Sequential Design to Fully Sequential Design}, journal = {Journal of Educational Measurement}, volume = {53}, number = {1}, year = {2016}, pages = {45{\textendash}62}, abstract = {Computerized adaptive testing (CAT) and multistage testing (MST) have become two of the most popular modes in large-scale computer-based sequential testing. ~Though most designs of CAT and MST exhibit strength and weakness in recent large-scale implementations, there is no simple answer to the question of which design is better because different modes may fit different practical situations. This article proposes a hybrid adaptive framework to combine both CAT and MST, inspired by an analysis of the history of CAT and MST. The proposed procedure is a design which transitions from a group sequential design to a fully sequential design. This allows for the robustness of MST in early stages, but also shares the advantages of CAT in later stages with fine tuning of the ability estimator once its neighborhood has been identified. Simulation results showed that hybrid designs following our proposed principles provided comparable or even better estimation accuracy and efficiency than standard CAT and MST designs, especially for examinees at the two ends of the ability range.}, issn = {1745-3984}, doi = {10.1111/jedm.12100}, url = {http://dx.doi.org/10.1111/jedm.12100}, author = {Wang, Shiyu and Lin, Haiyan and Chang, Hua-Hua and Douglas, Jeff} } @conference {2079, title = {A Heuristic Of CAT Item Selection Procedure For Testlets}, booktitle = {Annual Conference of the International Association for Computerized Adaptive Testing}, year = {2011}, keywords = {CAT, shadow test, testlets}, author = {Yuehmei Chien and David Shin and Walter Denny Way} } @conference {2078, title = {High-throughput Health Status Measurement using CAT in the Era of Personal Genomics: Opportunities and Challenges}, booktitle = {Annual Conference of the International Association for Computerized Adaptive Testing}, year = {2011}, keywords = {CAT, health applications, PROMIS}, author = {Eswar Krishnan} } @article {2267, title = {Hypothetical use of multidimensional adaptive testing for the assessment of student achievement in PISA. }, journal = {Educational and Psychological Measurement}, volume = {71}, year = {2011}, pages = {503-522}, author = {Frey, A. and Seitz, N-N.} } @inbook {1862, title = {A hybrid simulation procedure for the development of CATs}, year = {2009}, note = {{PDF File, 258 KB}}, address = {D. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.}, author = {Nydick, S. W. and Weiss, D. J.} } @article {2271, title = {Hypothetischer Einsatz adaptiven Testens bei der Messung von Bildungsstandards in Mathematik [Hypothetical use of adaptive testing for the measurement of educational standards in mathematics] . }, journal = {Zeitschrift f{\"u}r Erziehungswissenschaft}, volume = {8}, year = {2007}, pages = {169-184}, author = {Frey, A. and Ehmke, T.} } @article {2217, title = {How Big Is Big Enough? Sample Size Requirements for CAST Item Parameter Estimation}, journal = {Applied Measurement in Education}, volume = {19}, number = {3}, year = {2006}, pages = {241-255}, doi = {10.1207/s15324818ame1903_5}, url = {http://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_5}, author = {Chuah, Siang Chee and F Drasgow and Luecht, Richard} } @conference {853, title = {Historique et concepts propres au testing adaptatif [Adaptive testing: Historical accounts and concepts]}, booktitle = {Presented at the 69th Congress of the Acfas. Sherbrooke: Association canadienne fran{\c c}aise pour l{\textquoteright}avancement des sciences (Acfas). [In French]}, year = {2002}, author = {Blais, J. G.} } @article {60, title = {Hypergeometric family and item overlap rates in computerized adaptive testing}, journal = {Psychometrika}, volume = {67}, number = {3}, year = {2002}, pages = {387-398}, abstract = {A computerized adaptive test (CAT) is usually administered to small groups of examinees at frequent time intervals. It is often the case that examinees who take the test earlier share information with examinees who will take the test later, thus increasing the risk that many items may become known. Item overlap rate for a group of examinees refers to the number of overlapping items encountered by these examinees divided by the test length. For a specific item pool, different item selection algorithms may yield different item overlap rates. An important issue in designing a good CAT item selection algorithm is to keep item overlap rate below a preset level. In doing so, it is important to investigate what the lowest rate could be for all possible item selection algorithms. In this paper we rigorously prove that if every item had an equal possibility to be selected from the pool in a fixed-length CAT, the number of overlapping item among any α randomly sampled examinees follows the hypergeometric distribution family for α >= 1. Thus, the expected values of the number of overlapping items among any randomly sampled α examinee can be calculated precisely. These values may serve as benchmarks in controlling item overlap rates for fixed-length adaptive tests. (PsycINFO Database Record (c) 2005 APA )}, keywords = {Adaptive Testing, Algorithms, Computer Assisted Testing, Taking, Test, Time On Task computerized adaptive testing}, author = {Chang, Hua-Hua and Zhang, J.} } @inbook {1921, title = {Het ontwerpen van adaptieve examens [Designing adaptive tests]}, year = {1999}, note = {[In Dutch]}, address = {J. M Pieters, Tj. Plomp, and L.E. Odenthal (Eds.), Twintig jaar Toegepaste Onderwijskunde: Een kaleidoscopisch overzicht van Twents onderwijskundig onderzoek (pp. 249-267). Enschede: Twente University Press.}, author = {van der Linden, W. J.} } @conference {1078, title = {A hybrid method for controlling item exposure in computerized adaptive testing}, booktitle = {Paper presented at the annual meeting of the Psychometric Society}, year = {1998}, address = {Urbana, IL}, author = {Nering, M. L. and Davey, T. and Thompson, T.} } @conference {1071, title = {A hybrid method for controlling item exposure in computerized adaptive testing}, booktitle = {Paper presented at the annual meeting of the Psychometric Society}, year = {1998}, address = {Urbana, IL}, author = {Nering, M. L. and Davey, T. and Thompson, T.} } @article {331, title = {Health status assessment for the twenty-first century: item response theory, item banking and computer adaptive testing}, journal = {Quality of Life Research}, volume = {6}, number = {6}, year = {1997}, note = {Revicki, D ACella, D FEnglandQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitationQual Life Res. 1997 Aug;6(6):595-600.}, month = {Aug}, pages = {595-600}, edition = {1997/08/01}, abstract = {Health status assessment is frequently used to evaluate the combined impact of human immunodeficiency virus (HIV) disease and its treatment on functioning and well-being from the patient{\textquoteright}s perspective. No single health status measure can efficiently cover the range of problems in functioning and well-being experienced across HIV disease stages. Item response theory (IRT), item banking and computer adaptive testing (CAT) provide a solution to measuring health-related quality of life (HRQoL) across different stages of HIV disease. IRT allows us to examine the response characteristics of individual items and the relationship between responses to individual items and the responses to each other item in a domain. With information on the response characteristics of a large number of items covering a HRQoL domain (e.g. physical function, and psychological well-being), and information on the interrelationships between all pairs of these items and the total scale, we can construct more efficient scales. Item banks consist of large sets of questions representing various levels of a HRQoL domain that can be used to develop brief, efficient scales for measuring the domain. CAT is the application of IRT and item banks to the tailored assessment of HRQoL domains specific to individual patients. Given the results of IRT analyses and computer-assisted test administration, more efficient and brief scales can be used to measure multiple domains of HRQoL for clinical trials and longitudinal observational studies.}, keywords = {*Health Status, *HIV Infections/diagnosis, *Quality of Life, Diagnosis, Computer-Assisted, Disease Progression, Humans, Psychometrics/*methods}, isbn = {0962-9343 (Print)}, author = {Revicki, D. A. and Cella, D. F.} } @conference {1034, title = {Heuristic-based CAT: Balancing item information, content and exposure}, booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education}, year = {1996}, address = {New York NY}, author = {Luecht, RM and Hadadi, A. and Nungester, R. J.} } @conference {1032, title = {Heuristic-based CAT: Balancing item information, content, and exposure}, booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education}, year = {1996}, address = {New York NY}, author = {Luecht, RM and Hadadi, A. and Nungester, R. J.} } @conference {1035, title = {Heuristics based CAT: Balancing item information, content, and exposure}, booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education}, year = {1996}, address = {New York NY}, author = {Luecht, RM and Nungester, R. J. and Hadadi, A.} } @conference {375, title = {The historical developments of fit and its assessment in the computerized adaptive testing environment}, booktitle = {Midwestern Education Research Association annual meeting}, year = {1994}, month = {10/1994}, address = {Chicago, IL USA}, author = {Stone, G. E.} } @conference {1230, title = {How review options and administration mode influence scores on computerized vocabulary tests}, booktitle = {Paper presented at the annual meeting of the National Council on Measurement in Education}, year = {1992}, note = {$\#$VI92-01}, address = {San Francisco CA}, author = {Vispoel, W. P. and Wang, T. and De la Torre, R. and Bleiler, T. and Dings, J.} } @article {531, title = {Hardware and software evolution of an adaptive ability measurement system}, journal = {Behavior Research Methods and Instrumentation}, volume = {8}, year = {1976}, pages = {104-107}, author = {DeWitt, L. J. and Weiss, D. J.} }