01395nas a2200181 4500008004500000022001400045245008700059210006900146490000700215520080200222653003401024653002501058653001901083653001901102653001601121100002101137856005501158 2024 Engldsh  a2165-659200aThe Influence of Computerized Adaptive Testing on Psychometric Theory and Practice0 aInfluence of Computerized Adaptive Testing on Psychometric Theor0 v113 a

The major premise of this article is that part of the stimulus for the evolution of psychometric theory since the 1950s was the introduction of the concept of computerized adaptive testing (CAT) or its earlier non-CAT variations. The conceptual underpinnings of CAT that had the most influence on psychometric theory was the shift of emphasis from the test (or test score) as the focus of analysis to the test item (or item score). The change in focus allowed a change in the way that test results are conceived of as measurements. It also resolved the conflict among a number of ideas that were present in the early work on psychometric theory. Some of the conflicting ideas are summarized below to show how work on the development of CAT resolved some of those conflicts.

 

10acomputerized adaptive testing10aItem Response Theory10aparadigm shift10ascaling theory10atest design1 aReckase, Mark, D uhttps://jcatpub.net/index.php/jcat/issue/view/34/900538nas a2200181 4500008004500000022001400045245004000059210004000099260001200139300000800151490000600159653003300165653003000198653002000228653002700248100002200275856005900297 2022 Engldsh  a2165-659200aImproving Precision of CAT Measures0 aImproving Precision of CAT Measures c10/2022 a1-70 v910a: dichotomously scored items10aoption probability theory10ascoring methods10asubjective probability1 aBarnard, John, J. uhttp://mail.iacat.org/improving-precision-cat-measures02111nas a2200193 4500008003900000245007100039210006900110300000900179490000700188520153100195653000701726653003201733653001701765653002301782100001501805700001501820700001901835856006301854 2020 d00aItem Calibration Methods With Multiple Subscale Multistage Testing0 aItem Calibration Methods With Multiple Subscale Multistage Testi a3-280 v573 aAbstract Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait (θ) estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to calibrate items using the incomplete data from MST design. Further complication arises when there are multiple correlated subscales per test, and when items from different subscales need to be calibrated according to their respective score reporting metric. The current calibration-per-subscale method produced biased item parameters, and there is no available method for resolving the challenge. Deriving from the missing data principle, we showed when calibrating all items together the Rubin's ignorability assumption is satisfied such that the traditional single-group calibration is sufficient. When calibrating items per subscale, we proposed a simple modification to the current calibration-per-subscale method that helps reinstate the missing-at-random assumption and therefore corrects for the estimation bias that is otherwise existent. Three mainstream calibration methods are discussed in the context of MST, they are the marginal maximum likelihood estimation, the expectation maximization method, and the fixed parameter calibration. An extensive simulation study is conducted and a real data example from NAEP is analyzed to provide convincing empirical evidence.10aEM10amarginal maximum likelihood10amissing data10amultistage testing1 aWang, Chun1 aChen, Ping1 aJiang, Shengyu uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1224101507nas a2200157 4500008003900000245011800039210006900157300001200226490000700238520096800245100001901213700002001232700002101252700001301273856006301286 2020 d00aItem Selection and Exposure Control Methods for Computerized Adaptive Testing with Multidimensional Ranking Items0 aItem Selection and Exposure Control Methods for Computerized Ada a343-3690 v573 aAbstract The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across items). To address these issues, we introduce subpool partition strategies for item selection and within-person statement exposure control procedures. Simulations showed that the multinomial method reduces computation time while maintaining measurement precision. Both the freeze and revised Sympson-Hetter online (RSHO) methods controlled the statement exposure rate; RSHO sacrificed some measurement precision but increased pool use. Furthermore, preventing a statement's repetition on consecutive items neither hindered the effectiveness of the freeze or RSHO method nor reduced measurement precision.1 aChen, Chia-Wen1 aWang, Wen-Chung1 aChiu, Ming, Ming1 aRo, Sage uhttps://onlinelibrary.wiley.com/doi/abs/10.1111/jedm.1225201544nas a2200145 4500008003900000245009800039210006900137300001200206490000700218520104000225100002901265700002501294700003401319856004501353 2019 d00aImputation Methods to Deal With Missing Responses in Computerized Adaptive Multistage Testing0 aImputation Methods to Deal With Missing Responses in Computerize a495-5110 v793 aRouting examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated multiple missing data methods in computerized adaptive multistage testing, including two imputation techniques, the use of full information maximum likelihood and the use of scoring missing data as incorrect. These methods were examined under the missing completely at random, missing at random, and missing not at random frameworks, as well as other testing conditions. Comparisons were made to baseline conditions where no missing data were present. The results showed that imputation and the full information maximum likelihood methods outperformed incorrect scoring methods in terms of average bias, average root mean square error, and correlation between estimated and true thetas.1 aCetin-Berber, Dee, Duygu1 aSari, Halil, Ibrahim1 aHuggins-Manley, Anne, Corinne uhttps://doi.org/10.1177/001316441880553202022nas a2200193 4500008003900000245010500039210006900144300001200213490000700225520140200232100002301634700001901657700001801676700002101694700002201715700002801737700001801765856004501783 2019 d00aAn Investigation of Exposure Control Methods With Variable-Length CAT Using the Partial Credit Model0 aInvestigation of Exposure Control Methods With VariableLength CA a624-6380 v433 aThe purpose of this simulation study was to investigate the effect of several different item exposure control procedures in computerized adaptive testing (CAT) with variable-length stopping rules using the partial credit model. Previous simulation studies on CAT exposure control methods with polytomous items rarely considered variable-length tests. The four exposure control techniques examined were the randomesque with a group of three items, randomesque with a group of six items, progressive-restricted standard error (PR-SE), and no exposure control. The two variable-length stopping rules included were the SE and predicted standard error reduction (PSER), along with three item pools of varied sizes (43, 86, and 172 items). Descriptive statistics on number of nonconvergent cases, measurement precision, testing burden, item overlap, item exposure, and pool utilization were calculated. Results revealed that the PSER stopping rule administered fewer items on average while maintaining measurement precision similar to the SE stopping rule across the different item pool sizes and exposure controls. The PR-SE exposure control procedure surpassed the randomesque methods by further reducing test overlap, maintaining maximum exposure rates at the target rate or lower, and utilizing all items from the pool with a minimal increase in number of items administered and nonconvergent cases.1 aLeroux, Audrey, J.1 aWaid-Ebbs, Kay1 aWen, Pey-Shan1 aHelmer, Drew, A.1 aGraham, David, P.1 aO’Connor, Maureen, K.1 aRay, Kathleen uhttps://doi.org/10.1177/014662161882485601341nas a2200133 4500008003900000245010900039210006900148300001200217490000700229520088900236100001801125700001901143856004501162 2019 d00aItem Selection Criteria With Practical Constraints in Cognitive Diagnostic Computerized Adaptive Testing0 aItem Selection Criteria With Practical Constraints in Cognitive  a335-3570 v793 aFor item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP\_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP\_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.1 aLin, Chuan-Ju1 aChang, Hua-Hua uhttps://doi.org/10.1177/001316441879063400444nas a2200145 4500008004500000245005100045210005100096260001200147300001000159490000600169100002200175700001800197700002300215856006000238 2018 Engldsh 00aImplementing Three CATs Within Eighteen Months0 aImplementing Three CATs Within Eighteen Months c09/2018 a38-550 v61 aSpoden, Christian1 aFrey, Andreas1 aBernhardt, Raphael uhttp://iacat.org/jcat/index.php/jcat/article/view/70/3301331nas a2200121 4500008003900000245010900039210006900148300002100217520088900238100001801127700001901145856004501164 2018 d00aItem Selection Criteria With Practical Constraints in Cognitive Diagnostic Computerized Adaptive Testing0 aItem Selection Criteria With Practical Constraints in Cognitive  a00131644187906343 aFor item selection in cognitive diagnostic computerized adaptive testing (CD-CAT), ideally, a single item selection index should be created to simultaneously regulate precision, exposure status, and attribute balancing. For this purpose, in this study, we first proposed an attribute-balanced item selection criterion, namely, the standardized weighted deviation global discrimination index (SWDGDI), and subsequently formulated the constrained progressive index (CP\_SWDGDI) by casting the SWDGDI in a progressive algorithm. A simulation study revealed that the SWDGDI method was effective in balancing attribute coverage and the CP\_SWDGDI method was able to simultaneously balance attribute coverage and item pool usage while maintaining acceptable estimation precision. This research also demonstrates the advantage of a relatively low number of attributes in CD-CAT applications.1 aLin, Chuan-Ju1 aChang, Hua-Hua uhttps://doi.org/10.1177/001316441879063401840nas a2200157 4500008003900000245010800039210006900147300001200216490000700228520134100235100001501576700001601591700001301607700001701620856004501637 2018 d00aItem Selection Methods in Multidimensional Computerized Adaptive Testing With Polytomously Scored Items0 aItem Selection Methods in Multidimensional Computerized Adaptive a677-6940 v423 aMultidimensional computerized adaptive testing (MCAT) has been developed over the past decades, and most of them can only deal with dichotomously scored items. However, polytomously scored items have been broadly used in a variety of tests for their advantages of providing more information and testing complicated abilities and skills. The purpose of this study is to discuss the item selection algorithms used in MCAT with polytomously scored items (PMCAT). Several promising item selection algorithms used in MCAT are extended to PMCAT, and two new item selection methods are proposed to improve the existing selection strategies. Two simulation studies are conducted to demonstrate the feasibility of the extended and proposed methods. The simulation results show that most of the extended item selection methods for PMCAT are feasible and the new proposed item selection methods perform well. Combined with the security of the pool, when two dimensions are considered (Study 1), the proposed modified continuous entropy method (MCEM) is the ideal of all in that it gains the lowest item exposure rate and has a relatively high accuracy. As for high dimensions (Study 2), results show that mutual information (MUI) and MCEM keep relatively high estimation accuracy, and the item exposure rates decrease as the correlation increases.1 aTu, Dongbo1 aHan, Yuting1 aCai, Yan1 aGao, Xuliang uhttps://doi.org/10.1177/014662161876274803184nas a2200157 4500008004100000245010000041210006900141260005500210520260800265653002002873653001602893653001102909100001902920700001602939856007102955 2017 eng d00aThe Implementation of Nationwide High Stakes Computerized (adaptive) Testing in the Netherlands0 aImplementation of Nationwide High Stakes Computerized adaptive T aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

In this presentation the challenges of implementation of (adaptive) digital testing in the Facet system in the Netherlands is discussed. In the Netherlands there is a long tradition of implementing adaptive testing in educational settings. Already since the late nineties of the last century adaptive testing was used mostly in low stakes testing. Several CATs were implemented in student monitoring systems for primary education and in the general subjects language and arithmetic in vocational education. The only nationwide implemented high stakes CAT is the WISCAT-pabo: an arithmetic test for students in the first year of primary school teacher colleges. The psychometric advantages of item based adaptive testing are obvious. For example efficiency and high measurement precision. But there are also some disadvantages such as the impossibility of reviewing items during and after the test. During the test the student is not in control of his own test; e.q . he can only navigate forward to the next item. This is one of the reasons other methods of testing, such as multistage-testing, with adaptivity not on the item level but on subtest level, has become more popular to use in high stakes testing.

A main challenge of computerized (adaptive) testing is the implementation of the item bank and the test workflow in a digital system. Since 2014 a nationwide new digital system (Facet) was introduced in the Netherlands, with connections to the digital systems of different parties based on international standards (LTI and QTI). The first nationwide tests in the Facet-system were flexible exams Dutch and arithmetic for vocational (and secondary) education, taken as item response theory-based equated linear multiple forms tests, which are administered during 5 periods in a year. Nowadays there are some implementations of different methods of (multistage) adaptive testing in the same Facet system (DTT en Acet).

In this conference, other presenters of Cito will elaborate on the psychometric characteristics of this other adaptive testing methods. In this contribution, the system architecture and interoperability of the Facet system will be explained. The emphasis is on the implementation and the problems to be solved by using this digital system in all phases of the (adaptive) testing process: item banking, test construction, designing, publication, test taking, analyzing and reporting to the student. An evaluation of the use of the system will be presented.

Session Video

10aHigh stakes CAT10aNetherlands10aWISCAT1 avan Boxel, Mia1 aEggen, Theo uhttps://drive.google.com/open?id=1Kn1PvgioUYaOJ5pykq-_XWnwDU15rRsf03610nas a2200169 4500008004100000245006900041210006600110260005500176520302300231653000803254653002403262653003303286100001503319700001803334700001703352856007103369 2017 eng d00aAn Imputation Approach to Handling Incomplete Computerized Tests0 aImputation Approach to Handling Incomplete Computerized Tests aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

As technology advances, computerized adaptive testing (CAT) is becoming increasingly popular as it allows tests to be tailored to an examinee’s ability.  Nevertheless, examinees might devise testing strategies to use CAT to their advantage.  For instance, if only the items that examinees answer count towards their score, then a higher theta score might be obtained by spending more time on items at the beginning of the test and skipping items at the end if time runs out. This type of gaming can be discouraged if examinees’ scores are lowered or “penalized” based on the amount of non-response.

The goal of this study was to devise a penalty function that would meet two criteria: 1) the greater the omit rate, the greater the penalty, and 2) examinees with the same ability and the same omit rate should receive the same penalty. To create the penalty, theta was calculated based on only the items the examinee responded to ( ).  Next, the expected number correct score (EXR) was obtained using  and the test characteristic curve. A penalized expected number correct score (E ) was obtained by multiplying EXR by the proportion of items the examinee responded to. Finally, the penalized theta ( ) was identified using the test characteristic curve. Based on   and the item parameters ( ) of an unanswered item, the likelihood of a correct response,  , is computed and employed to estimate the imputed score ( ) for the unanswered item.

Two datasets were used to generate tests with completion rates of 50%, 80%, and 90%.  The first dataset included real data where approximately 4,500 examinees responded to a 21 -item test which provided a baseline/truth. Sampling was done to achieve the three completion rate conditions. The second dataset consisted of simulated item scores for 50,000 simulees under a 1-2-4 multi-stage CAT design where each stage contained seven items. Imputed item scores for unanswered items were computed using a variety of values for G (and therefore T).  Three other approaches to handling unanswered items were also considered: all correct (i.e., T = 0), all incorrect (i.e., T = 1), and random scoring (i.e., T = 0.5).

The current study investigated the impact on theta estimates resulting from the proposed approach to handling unanswered items in a fixed-length CAT. In real testing situations, when examinees do not finish a test, it is hard to tell whether they tried diligently but ran out of time or whether they attempted to manipulate the scoring engine.  To handle unfinished tests with penalties, the proposed approach considers examinees’ abilities and incompletion rates. The results of this study provide direction for psychometric practitioners when considering penalties for omitted responses.

Session Video

10aCAT10aimputation approach10aincomplete computerized test1 aChen, Troy1 aHuang, Chi-Yu1 aLiu, Chunyan uhttps://drive.google.com/open?id=1vznZeO3nsZZK0k6_oyw5c9ZTP8uyGnXh01106nas 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/10.1177/014662161773039203841nas a2200145 4500008004100000245014000041210006900181260005500250520324600305653000803551653001103559653002903570100002503599856007103624 2017 eng d00aIssues in Trait Range Coverage for Patient Reported Outcome Measure CATs - Extending the Ceiling for Above-average Physical Functioning0 aIssues in Trait Range Coverage for Patient Reported Outcome Meas aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

The use of a measure which fails to cover the upper range of functioning may produce results which can lead to serious misinterpretation. Scores produced by such a measure may fail to recognize significant improvement, or may not be able to demonstrate functioning commensurate with an important milestone. Accurate measurement of this range is critical for the assessment of physically active adults, e.g., athletes recovering from injury and active military personnel who wish to return to active service. Alternatively, a PF measure with a low ceiling might fail to differentiate patients in rehabilitation who continue to improve, but for whom their score ceilings due to the measurement used.

The assessment of physical function (PF) has greatly benefited from modern psychometric theory and resulting scales, such as the Patient-Reported Outcomes Measurement Information System (PROMIS®) PF instruments. While PROMIS PF has extended the range of function upwards relative to older “legacy” instruments, few PROMIS PF items asses high levels of function. We report here on the development of higher functioning items for the PROMIS PF bank.

An expert panel representing orthopedics, sports/military medicine, and rehabilitation reviewed existing instruments and wrote new items. After internal review, cognitive interviews were conducted with 24 individuals of average and high levels of physical function. The remaining candidate items were administered along with 50 existing PROMIS anchor items to an internet panel screened for low, average, and high levels of physical function (N = 1,600), as well as members of Boston-area gyms (N= 344). The resulting data was subjected to standard psychometric analysis, along with multiple linking methods to place the new items on the existing PF metric. The new items were added to the full PF bank for simulated computerized adaptive testing (CAT).

Item response data was collected on 54 candidate items. Items that exhibited local dependence (LD) or differential item functioning (DIF) related to gender, age, race, education, or PF status. These items were removed from consideration. Of the 50 existing PROMIS PF items, 31 were free of DIF and LD and used as anchors. The parameters for the remaining new candidate items were estimated twice: freelyestimated and linked with coefficients and fixed-anchor calibration. Both methods were comparable and had appropriate fit. The new items were added to the full PF bank for simulated CATs. The resulting CAT was able to extend the ceiling with high precision to a T-score of 68, suggesting accurate measurement for 97% of the general population.

Extending the range of items by which PF is measured will substantially improve measurement quality, applicability, and efficiency. The bank has incorporated these extension items and is available for use in research and clinics for brief CAT administration (see www.healthmeasures.net). Future research projects should focus on recovery trajectories of the measure for individuals with above average function who are recovering from injury.

Session Video

10aCAT10aIssues10aPatient Reported Outcome1 aGershon, Richard, C. uhttps://drive.google.com/open?id=1ZC02F-dIyYovEjzpeuRdoXDiXMLFRuKb02155nas a2200145 4500008004100000245005100041210005100092260005500143520166100198653002301859653002001882100001901902700001301921856007501934 2017 eng d00aItem Parameter Drifting and Online Calibration0 aItem Parameter Drifting and Online Calibration aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Item calibration is a part of the most important topics in item response theory (IRT). Since many largescale testing programs have switched from paper and pencil (P&P) testing mode to computerized adaptive testing (CAT) mode, developing methods for efficiently calibrating new items have become vital. Among many proposed item calibration processes in CAT, online calibration is the most cost-effective. This presentation introduces an online (re)calibration design to detect item parameter drift for computerized adaptive testing (CAT) in both unidimensional and multidimensional environments. Specifically, for online calibration optimal design in unidimensional computerized adaptive testing model, a two-stage design is proposed by implementing a proportional density index algorithm. For a multidimensional computerized adaptive testing model, a four-quadrant online calibration pretest item selection design with proportional density index algorithm is proposed. Comparisons were made between different online calibration item selection strategies. Results showed that under unidimensional computerized adaptive testing, the proposed modified two-stage item selection criterion with the proportional density algorithm outperformed the other existing methods in terms of item parameter calibration and item parameter drift detection, and under multidimensional computerized adaptive testing, the online (re)calibration technique with the proposed four-quadrant item selection design with proportional density index outperformed other methods.

Session Video

10aonline calibration10aParameter Drift1 aChang, Hua-Hua1 aGuo, Rui uhttp://mail.iacat.org/item-parameter-drifting-and-online-calibration-001393nas a2200169 4500008004100000245003600041210003600077260005500113520088800168653000801056653002101064100002101085700001201106700001601118700001801134856007101152 2017 eng d00aItem Pool Design and Evaluation0 aItem Pool Design and Evaluation aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Early work on CAT tended to use existing sets of items which came from fixed length test forms. These sets of items were selected to meet much different requirements than are needed for a CAT; decision making or covering a content domain. However, there was also some early work that suggested having items equally distributed over the range of proficiency that was of interest or concentrated at a decision point. There was also some work that showed that there was bias in proficiency estimates when an item pool was too easy or too hard. These early findings eventually led to work on item pool design and, more recently, on item pool evaluation. This presentation gives a brief overview of these topics to give some context for the following presentations in this symposium.

Session Video

10aCAT10aItem Pool Design1 aReckase, Mark, D1 aHe, Wei1 aXu, Jing-Ru1 aZhou, Xuechun uhttps://drive.google.com/open?id=1ZAsqm1yNZlliqxEHcyyqQ_vOSu20xxZs03464nas a2200145 4500008004100000245004500041210004500086260005500131520301500186653000803201653001803209653001603227100001403243856006103257 2017 eng d00aItem Response Time on Task Effect in CAT0 aItem Response Time on Task Effect in CAT aNiigata, JapanbNiigata Seiryo Universityc08/20173 a

Introduction. In addition to reduced test length and increased measurement efficiency, computerized adaptive testing (CAT) can provide new insights into the cognitive process of task completion that cannot be mined via conventional tests. Response time is a primary characteristic of the task completion procedure. It has the potential to inform us about underlying processes. In this study, the relationship between response time and response accuracy will be investigated.

Hypothesis. The present study argues that the relationship between response time on task and response accuracy, which may be positive, negative, or curvilinear, will depend on cognitive nature of task items, holding ability of the subjects and difficulty of the items constant. The interpretations regarding the associations are not uniform either.

Research question. Is there a homogeneous effect of response time on test outcome across Graduate

Proposed explanations. If the accuracy of cognitive test responses decreases with response time, then it is an indication that the underlying cognitive process is a degrading process such as knowledge retrieval. More accessible knowledge can be retrieved faster than less accessible knowledge. It is inherent to knowledge retrieval that the success rate declines with elapsing response time. For instance, in reading tasks, the time on task effect is negative and the more negative, the easier a task is. However, if the accuracy of cognitive test responses increases with response time, then the process is of an upgrading nature, with an increasing success rate as a function of response time. For example, problem-solving takes time, and fast responses are less likely to be well-founded responses. It is of course also possible that the relationship is curvilinear, as when an increasing success rate is followed by a decreasing success rate or vice versa.

Methodology. The data are from computer-based GRE quantitative and verbal tests and will be analyzed with generalized linear mixed models (GLMM) framework after controlling the effect of ability and item difficulty as possible confounding factors. A linear model means a linear combination of predictors determining the probability of person p for answering item i correctly. The models are equivalent with advanced IRT models that go beyond the regular modeling of test responses in terms of one or more latent variables and item parameters. The lme4 package for R will be utilized to conduct the statistical calculation.

Implications. The right amount of testing time in CAT is important—too much is wasteful and costly, too little impacts score validity. The study is expected to provide new perception on the relationship between response time and response accuracy, which in turn, contribute to a better understanding of time effects and relevant cognitive process in CA.

Session Video

10aCAT10aResponse time10aTask effect1 aShi, Yang uhttp://mail.iacat.org/item-response-time-task-effect-cat01708nas a2200145 4500008004100000245006200041210006200103260005500165520122100220653000801441653001401449653003001463100002101493856004801514 2017 eng d00aItem Selection Strategies for Developing CAT in Indonesia0 aItem Selection Strategies for Developing CAT in Indonesia aNiigata JapanbNiiagata Seiryo Universityc08/20173 a

Recently, development of computerized testing in Indonesia is quiet promising for the future. Many government institutions used the technology for recruitment. Starting from Indonesian Army acknowledged the benefits of computerized adaptive testing (CAT) over conventional test administration, ones of the issues of selection the first item have taken place of attention. Due to CAT’s basic philosophy, several methods can be used to select the first item such as educational level, ability estimation from item simulation, or other methods. In this case, the question is remains how apply the methods most effective in the context of constrained adaptive testing. This paper reviews such strategies that appeared in the relevant literature. The focus of this paper is on studies that have been conducted in order to evaluate the effectiveness of item selection strategies for dichotomous scoring. In this paper, also discusses the strength and weaknesses of each strategy group using examples from simulation studies. No new research is presented but rather a compendium of models is reviewed in term of learning in the newcomer context, a wide view of first item selection strategies.

 

10aCAT10aIndonesia10aitem selection strategies1 aChandra, Istiani uhttps://www.youtube.com/watch?v=2KuFrRATq9Q00592nas a2200169 4500008003900000022001400039245011200053210006900165300001600234490000700250100002400257700002200281700002500303700002300328700002500351856004600376 2017 d a1573-264900aItem usage in a multidimensional computerized adaptive test (MCAT) measuring health-related quality of life0 aItem usage in a multidimensional computerized adaptive test MCAT a2909–29180 v261 aPaap, Muirne, C. S.1 aKroeze, Karel, A.1 aTerwee, Caroline, B.1 avan der Palen, Job1 aVeldkamp, Bernard, P uhttps://doi.org/10.1007/s11136-017-1624-301586nas a2200133 4500008003900000022001400039245008800053210006900141300001400210490000700224520115500231100002501386856004101411 2016 d a1745-398400aOn the Issue of Item Selection in Computerized Adaptive Testing With Response Times0 aIssue of Item Selection in Computerized Adaptive Testing With Re a212–2280 v533 aMany standardized tests are now administered via computer rather than paper-and-pencil format. The computer-based delivery mode brings with it certain advantages. One advantage is the ability to adapt the difficulty level of the test to the ability level of the test taker in what has been termed computerized adaptive testing (CAT). A second advantage is the ability to record not only the test taker's response to each item (i.e., question), but also the amount of time the test taker spends considering and answering each item. Combining these two advantages, various methods were explored for utilizing response time data in selecting appropriate items for an individual test taker.Four strategies for incorporating response time data were evaluated, and the precision of the final test-taker score was assessed by comparing it to a benchmark value that did not take response time information into account. While differences in measurement precision and testing times were expected, results showed that the strategies did not differ much with respect to measurement precision but that there were differences with regard to the total testing time.1 aVeldkamp, Bernard, P uhttp://dx.doi.org/10.1111/jedm.1211000516nas a2200193 4500008004500000022001400045245004500059210004200104300000900146490000600155653001300161653001500174653001300189653001200202653001100214653001200225100002100237856006400258 2015 Engldsh  a2165-659200aImplementing a CAT: The AMC Experience 0 aImplementing a CAT The AMC Experience a1-120 v310aadaptive10aAssessment10acomputer10amedical10aonline10aTesting1 aBarnard, John, J uhttp://www.iacat.org/jcat/index.php/jcat/article/view/52/2501415nas a2200169 4500008003900000245007000039210006900109300001400178490000700192520091000199100001901109700002101128700001601149700001201165700001401177856005401191 2015 d00aInvestigation of Response Changes in the GRE Revised General Test0 aInvestigation of Response Changes in the GRE Revised General Tes a1002-10200 v753 aResearch on examinees’ response changes on multiple-choice tests over the past 80 years has yielded some consistent findings, including that most examinees make score gains by changing answers. This study expands the research on response changes by focusing on a high-stakes admissions test—the Verbal Reasoning and Quantitative Reasoning measures of the GRE revised General Test. We analyzed data from 8,538 examinees for Quantitative and 9,140 for Verbal sections who took the GRE revised General Test in 12 countries. The analyses yielded findings consistent with prior research. In addition, as examinees’ ability increases, the benefit of response changing increases. The study yielded significant implications for both test agencies and test takers. Computer adaptive tests often do not allow the test takers to review and revise. Findings from this study confirm the benefit of such features.1 aLiu, Ou, Lydia1 aBridgeman, Brent1 aGu, Lixiong1 aXu, Jun1 aKong, Nan uhttp://epm.sagepub.com/content/75/6/1002.abstract01984nas a2200121 4500008003900000245008900039210006900128300001200197490000700209520157400216100001501790856005701805 2014 d00aImproving Measurement Precision of Hierarchical Latent Traits Using Adaptive Testing0 aImproving Measurement Precision of Hierarchical Latent Traits Us a452-4770 v393 a

Many latent traits in social sciences display a hierarchical structure, such as intelligence, cognitive ability, or personality. Usually a second-order factor is linearly related to a group of first-order factors (also called domain abilities in cognitive ability measures), and the first-order factors directly govern the actual item responses. Because only a subtest of items is used to measure each domain, the lack of sufficient reliability becomes the primary impediment for generating and reporting domain abilities. In recent years, several item response theory (IRT) models have been proposed to account for hierarchical factor structures, and these models are also shown to alleviate the low reliability issue by using in-test collateral information to improve measurement precision. This article advocates using adaptive item selection together with a higher order IRT model to further increase the reliability of hierarchical latent trait estimation. Two item selection algorithms are proposed—the constrained D-optimal method and the sequencing domain method. Both are shown to yield improved measurement precision as compared to the unidimensional item selection (by treating each dimension separately). The improvement is more prominent when the test length is short and when the correlation between dimensions is high (e.g., higher than .64). Moreover, two reliability indices for hierarchical latent traits are discussed and their use for quantifying the reliability of hierarchical traits measured by adaptive testing is demonstrated.

1 aWang, Chun uhttp://jeb.sagepub.com/cgi/content/abstract/39/6/45201730nas a2200133 4500008003900000245008300039210006900122300001200191490000700203520130000210100001201510700002101522856005301543 2014 d00aItem Pool Design for an Operational Variable-Length Computerized Adaptive Test0 aItem Pool Design for an Operational VariableLength Computerized  a473-4940 v743 a

For computerized adaptive tests (CATs) to work well, they must have an item pool with sufficient numbers of good quality items. Many researchers have pointed out that, in developing item pools for CATs, not only is the item pool size important but also the distribution of item parameters and practical considerations such as content distribution and item exposure issues. Yet, there is little research on how to design item pools to have those desirable features. The research reported in this article provided step-by-step hands-on guidance on the item pool design process by applying the bin-and-union method to design item pools for a large-scale licensure CAT employing complex adaptive testing algorithm with variable test length, a decision based on stopping rule, content balancing, and exposure control. The design process involved extensive simulations to identify several alternative item pool designs and evaluate their performance against a series of criteria. The design output included the desired item pool size and item parameter distribution. The results indicate that the mechanism used to identify the desirable item pool features functions well and that two recommended item pool designs would support satisfactory performance of the operational testing program.

1 aHe, Wei1 aReckase, Mark, D uhttp://epm.sagepub.com/content/74/3/473.abstract01545nas a2200145 4500008003900000245011500039210006900154300001200223490000700235520102700242100002601269700002601295700002501321856005301346 2014 d00aItem Selection Methods Based on Multiple Objective Approaches for Classifying Respondents Into Multiple Levels0 aItem Selection Methods Based on Multiple Objective Approaches fo a187-2000 v383 a

Computerized classification tests classify examinees into two or more levels while maximizing accuracy and minimizing test length. The majority of currently available item selection methods maximize information at one point on the ability scale, but in a test with multiple cutting points selection methods could take all these points simultaneously into account. If for each cutting point one objective is specified, the objectives can be combined into one optimization function using multiple objective approaches. Simulation studies were used to compare the efficiency and accuracy of eight selection methods in a test based on the sequential probability ratio test. Small differences were found in accuracy and efficiency between different methods depending on the item pool and settings of the classification method. The size of the indifference region had little influence on accuracy but considerable influence on efficiency. Content and exposure control had little influence on accuracy and efficiency.

1 avan Groen, Maaike, M.1 aEggen, Theo, J. H. M.1 aVeldkamp, Bernard, P uhttp://apm.sagepub.com/content/38/3/187.abstract01409nas a2200157 4500008003900000245009300039210006900132300001000201490000700211520091300218100002301131700001501154700001701169700001301186856005201199 2013 d00aThe Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing0 aInfluence of Item Calibration Error on VariableLength Computeriz a24-400 v373 a

Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be “tailored” to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends on the item parameter values. However, items are chosen on the basis of their parameter estimates, and capitalization on chance may occur. In this article, the authors investigated the effects of capitalization on chance on test length and classification accuracy in several VL-CAT simulations. The results confirm that capitalization on chance occurs in VL-CAT and has complex effects on test length, ability estimation, and classification accuracy. These results have important implications for the design and implementation of VL-CATs.

1 aPatton, Jeffrey, M1 aYing Cheng1 aYuan, Ke-Hai1 aDiao, Qi uhttp://apm.sagepub.com/content/37/1/24.abstract01277nas a2200133 4500008003900000245006600039210006500105300001200170490000700182520086900189100001301058700001901071856005301090 2013 d00aIntegrating Test-Form Formatting Into Automated Test Assembly0 aIntegrating TestForm Formatting Into Automated Test Assembly a361-3740 v373 a

Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using a simultaneous optimization model is more attractive than any of the current, more time-consuming two-stage processes. The goal of this study was to provide such simultaneous models both for computer-delivered and paper forms, as well as explore their performances relative to two-stage optimization. Empirical examples are presented to show that it is possible to automatically produce fully formatted optimal test forms directly from item pools up to some 2,000 items on a regular PC in realistic times.

1 aDiao, Qi1 aLinden, Wim, J uhttp://apm.sagepub.com/content/37/5/361.abstract00534nas a2200145 4500008004100000245009500041210006900136300001000205490000600215100001900221700001100240700001000251700001300261856011400274 2013 en d00aItem Ordering in Stochastically Curtailed Health Questionnaires With an Observable Outcome0 aItem Ordering in Stochastically Curtailed Health Questionnaires  a38-660 v11 aFinkelman, M D1 aKim, W1 aHe, Y1 aLai, A M uhttp://mail.iacat.org/content/item-ordering-stochastically-curtailed-health-questionnaires-observable-outcome01492nas 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

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.

1 aHan, Kyung, T uhttp://apm.sagepub.com/content/37/4/259.abstract00518nas a2200109 4500008004500000245012600045210006900171100001700240700001900257700001600276856011600292 2012 Engldsh 00aImproving personality facet scores with multidimensional computerized adaptive testing: An illustration with the NEO PI-R0 aImproving personality facet scores with multidimensional compute1 aMakransky, G1 aMortensen, E L1 aGlas, C A W uhttp://mail.iacat.org/content/improving-personality-facet-scores-multidimensional-computerized-adaptive-testing01089nas a2200157 4500008003900000022001400039245007000053210006900123300001400192490000700206520061300213100001600826700001700842700001700859856005500876 2012 d a1745-398400aInvestigating the Effect of Item Position in Computer-Based Tests0 aInvestigating the Effect of Item Position in ComputerBased Tests a362–3790 v493 a

Computer-based tests (CBTs) often use random ordering of items in order to minimize item exposure and reduce the potential for answer copying. Little research has been done, however, to examine item position effects for these tests. In this study, different versions of a Rasch model and different response time models were examined and applied to data from a CBT administration of a medical licensure examination. The models specifically were used to investigate whether item position affected item difficulty and item intensity estimates. Results indicated that the position effect was negligible.

1 aLi, Feiming1 aCohen, Allan1 aShen, Linjun uhttp://dx.doi.org/10.1111/j.1745-3984.2012.00181.x01289nas a2200109 4500008004500000245009100045210006900136490000700205520083400212100001501046856011801061 2012 Engldsh 00aItem Overexposure in Computerized Classification Tests Using Sequential Item Selection0 aItem Overexposure in Computerized Classification Tests Using Seq0 v173 a

Computerized classification tests (CCTs) often use sequential item selection which administers items according to maximizing psychometric information at a cut point demarcating passing and failing scores. This paper illustrates why this method of item selection leads to the overexposure of a significant number of items, and the performances of three different methods for controlling maximum item exposure rates in CCTs are compared. Specifically, the Sympson-Hetter, restricted, and item eligibility methods are examined in two studies realistically simulating different types of CCTs and are evaluated based upon criteria including classification accuracy, the number of items exceeding the desired maximum exposure rate, and test overlap. The pros and cons of each method are discussed from a practical perspective.

1 aHuebner, A uhttp://mail.iacat.org/content/item-overexposure-computerized-classification-tests-using-sequential-item-selection00442nas a2200121 4500008003900000245008600039210006900125300001200194490000700206100001800213700002100231856006800252 2012 d00aItem Selection and Ability Estimation Procedures for a Mixed-Format Adaptive Test0 aItem Selection and Ability Estimation Procedures for a MixedForm a305-3260 v251 aHo, Tsung-Han1 aDodd, Barbara, G uhttp://www.tandfonline.com/doi/abs/10.1080/08957347.2012.71468600775nas a2200145 4500008004100000245005700041210005700098260001200155520031700167653001500484100001700499700001300516700001900529856008100548 2011 eng d00aImpact of Item Drift on Candidate Ability Estimation0 aImpact of Item Drift on Candidate Ability Estimation c10/20113 a

For large operational pools, candidate ability estimates appear robust to item drift, especially under conditions that may represent ‘normal’ amounts of drift. Even with ‘extreme’ conditions of drift (e.g., 20% of items drifting 1.00 logits), decision consistency was still high.

10aitem drift1 aHagge, Sarah1 aWoo, Ada1 aDickison, Phil uhttp://mail.iacat.org/content/impact-item-drift-candidate-ability-estimation00654nas a2200157 4500008004100000020001400041245015700055210006900212100001800281700001400299700001500313700001600328700001500344700001300359856012400372 2011 eng d a1073-191100aItem banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): depression, anxiety, and anger0 aItem banks for measuring emotional distress from the PatientRepo1 aPilkonis, P A1 aChoi, S W1 aReise, S P1 aStover, A M1 aRiley, W T1 aCella, D uhttp://mail.iacat.org/content/item-banks-measuring-emotional-distress-patient-reported-outcomes-measurement-information01700nas a2200121 4500008003900000245009500039210006900134300001000203490000700213520128800220100001801508856005201526 2011 d00aItem Selection Criteria With Practical Constraints for Computerized Classification Testing0 aItem Selection Criteria With Practical Constraints for Computeri a20-360 v713 a

This study compares four item selection criteria for a two-category computerized classification testing: (1) Fisher information (FI), (2) Kullback—Leibler information (KLI), (3) weighted log-odds ratio (WLOR), and (4) mutual information (MI), with respect to the efficiency and accuracy of classification decision using the sequential probability ratio test as well as the extent of item usage. The comparability of the four item selection criteria are examined primarily under three types of item selection conditions: (1) using only the four item selection algorithms, (2) using the four item selection algorithms and content balancing control, and (3) using the four item selection algorithms, content balancing control, and item exposure control. The comparability of the four item selection criteria is also evaluated in two types of proficiency distribution and three levels of indifference region width. The results show that the differences of the four item selection criteria are washed out as more realistic constraints are imposed. Moreover, within two-category classification testing, the use of MI does not necessarily generate greater efficiency than FI, WLOR, and KLI, although MI might seem attractive for its general form of formula in item selection.

1 aLin, Chuan-Ju uhttp://epm.sagepub.com/content/71/1/20.abstract01252nas a2200181 4500008004100000245012100041210006900162260001200231520055600243653003300799653000800832653001900840653003500859100001800894700001600912700002200928856012000950 2011 eng d00aItem Selection Methods based on Multiple Objective Approaches for Classification of Respondents into Multiple Levels0 aItem Selection Methods based on Multiple Objective Approaches fo c10/20113 a

Is it possible to develop new item selection methods which take advantage of the fact that we want to classify into multiple categories? New methods: Taking multiple points on the ability scale into account; Based on multiple objective approaches.

Conclusions

10aadaptive classification test10aCAT10aitem selection10asequential classification test1 aGroen, Maaike1 aEggen, Theo1 aVeldkamp, Bernard uhttp://mail.iacat.org/content/item-selection-methods-based-multiple-objective-approaches-classification-respondents00428nas a2200097 4500008004100000245008300041210006900124300001200193100001600205856010900221 2010 eng d00aImplementing the Graduate Management Admission Test Computerized Adaptive Test0 aImplementing the Graduate Management Admission Test Computerized a151-1661 aRudner, L M uhttp://mail.iacat.org/content/implementing-graduate-management-admission-test-computerized-adaptive-test01417nas a2200121 4500008003900000245015400039210006900193300001200262490000700274520094600281100001501227856005301242 2010 d00aImproving Cognitive Diagnostic Computerized Adaptive Testing by Balancing Attribute Coverage: The Modified Maximum Global Discrimination Index Method0 aImproving Cognitive Diagnostic Computerized Adaptive Testing by  a902-9130 v703 a

This article proposes a new item selection method, namely, the modified maximum global discrimination index (MMGDI) method, for cognitive diagnostic computerized adaptive testing (CD-CAT). The new method captures two aspects of the appeal of an item: (a) the amount of contribution it can make toward adequate coverage of every attribute and (b) the amount of contribution it can make toward recovering the latent cognitive profile. A simulation study shows that the new method ensures adequate coverage of every attribute, which improves the validity of the test scores, and defensibility of the proposed uses of the test. Furthermore, compared with the original global discrimination index method, the MMGDI method improves the recovery rate of each attribute and of the entire cognitive profile, especially the latter. Therefore, the new method improves both the validity and reliability of the test scores from a CD-CAT program.

1 aYing Cheng uhttp://epm.sagepub.com/content/70/6/902.abstract00415nas a2200133 4500008004100000245004600041210004600087300001200133100001800145700001600163700001300179700001700192856007200209 2010 eng d00aInnovative Items for Computerized Testing0 aInnovative Items for Computerized Testing a215-2301 aParshall, C G1 aHarmes, J C1 aDavey, T1 aPashley, P J uhttp://mail.iacat.org/content/innovative-items-computerized-testing00399nas a2200097 4500008004100000245007300041210006900114300001200183100001300195856009300208 2010 eng d00aThe Investigation of Differential Item Functioning in Adaptive Tests0 aInvestigation of Differential Item Functioning in Adaptive Tests a331-3521 aZwick, R uhttp://mail.iacat.org/content/investigation-differential-item-functioning-adaptive-tests00353nas a2200097 4500008004100000245005200041210005200093300001200145100001600157856008200173 2010 eng d00aItem Parameter Estimation and Item Fit Analysis0 aItem Parameter Estimation and Item Fit Analysis a269-2881 aGlas, C A W uhttp://mail.iacat.org/content/item-parameter-estimation-and-item-fit-analysis00450nas a2200121 4500008004100000245006200041210006200103260002300165300000900188100002300197700001700220856009100237 2010 eng d00aItem Selection and Ability Estimation in Adaptive Testing0 aItem Selection and Ability Estimation in Adaptive Testing aNew YorkbSpringer a3-301 avan der Linden, WJ1 aPashley, P J uhttp://mail.iacat.org/content/item-selection-and-ability-estimation-adaptive-testing-001512nas a2200217 4500008004100000245008100041210006900122300001200191490000700203520078900210653001100999653003401010653002201044653003501066653002101101653002101122100001901143700001401162700001601176856010201192 2010 eng d00aItem Selection and Hypothesis Testing for the Adaptive Measurement of Change0 aItem Selection and Hypothesis Testing for the Adaptive Measureme a238-2540 v343 a

Assessing individual change is an important topic in both psychological and educational measurement. An adaptive measurement of change (AMC) method had previously been shown to exhibit greater efficiency in detecting change than conventional nonadaptive methods. However, little work had been done to compare different procedures within the AMC framework. This study introduced a new item selection criterion and two new test statistics for detecting change with AMC that were specifically designed for the paradigm of hypothesis testing. In two simulation sets, the new methods for detecting significant change improved on existing procedures by demonstrating better adherence to Type I error rates and substantially better power for detecting relatively small change. 

10achange10acomputerized adaptive testing10aindividual change10aKullback–Leibler information10alikelihood ratio10ameasuring change1 aFinkelman, M D1 aWeiss, DJ1 aKim-Kang, G uhttp://mail.iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change-001387nas a2200241 4500008004100000020002700041245005000068210005000118250001500168300001000183490000600193520067500199653002600874653001100900653004200911653002400953653001800977653002000995653001901015100001501034700001601049856008001065 2009 eng d a1548-5951 (Electronic)00aItem response theory and clinical measurement0 aItem response theory and clinical measurement a2008/11/04 a27-480 v53 aIn this review, we examine studies that use item response theory (IRT) to explore the psychometric properties of clinical measures. Next, we consider how IRT has been used in clinical research for: scale linking, computerized adaptive testing, and differential item functioning analysis. Finally, we consider the scale properties of IRT trait scores. We conclude that there are notable differences between cognitive and clinical measures that have relevance for IRT modeling. Future research should be directed toward a better understanding of the metric of the latent trait and the psychological processes that lead to individual differences in item response behaviors.10a*Psychological Theory10aHumans10aMental Disorders/diagnosis/psychology10aPsychological Tests10aPsychometrics10aQuality of Life10aQuestionnaires1 aReise, S P1 aWaller, N G uhttp://mail.iacat.org/content/item-response-theory-and-clinical-measurement00557nas a2200121 4500008004100000245008100041210006900122260009700191100001700288700001400305700001600319856010000335 2009 eng d00aItem selection and hypothesis testing for the adaptive measurement of change0 aItem selection and hypothesis testing for the adaptive measureme aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aFinkelman, M1 aWeiss, DJ1 aKim-Kang, G uhttp://mail.iacat.org/content/item-selection-and-hypothesis-testing-adaptive-measurement-change01377nas a2200121 4500008003900000245005800039210005800097300001200155490000700167520100400174100002401178856005301202 2009 d00aItem Selection in Computerized Classification Testing0 aItem Selection in Computerized Classification Testing a778-7930 v693 a

Several alternatives for item selection algorithms based on item response theory in computerized classification testing (CCT) have been suggested, with no conclusive evidence on the substantial superiority of a single method. It is argued that the lack of sizable effect is because some of the methods actually assess items very similarly through different calculations and will usually select the same item. Consideration of methods that assess information across a wider range is often unnecessary under realistic conditions, although it might be advantageous to utilize them only early in a test. In addition, the efficiency of item selection approaches depend on the termination criteria that are used, which is demonstrated through didactic example and Monte Carlo simulation. Item selection at the cut score, which seems conceptually appropriate for CCT, is not always the most efficient option. A broad framework for item selection in CCT is presented that incorporates these points.

1 aThompson, Nathan, A uhttp://epm.sagepub.com/content/69/5/778.abstract01423nas a2200133 4500008004100000020001400041245005800055210005800113300001200171490000700183520099600190100001801186856008501204 2009 eng d a0013-164400aItem selection in computerized classification testing0 aItem selection in computerized classification testing a778-7930 v693 aSeveral alternatives for item selection algorithms based on item response theory in computerized classification testing (CCT) have been suggested, with no conclusive evidence on the substantial superiority of a single method. It is argued that the lack of sizable effect is because some of the methods actually assess items very similarly through different calculations and will usually select the same item. Consideration of methods that assess information across a wider range is often unnecessary under realistic conditions, although it might be advantageous to utilize them only early in a test. In addition, the efficiency of item selection approaches depend on the termination criteria that are used, which is demonstrated through didactic example and Monte Carlo simulation. Item selection at the cut score, which seems conceptually appropriate for CCT, is not always the most efficient option. A broad framework for item selection in CCT is presented that incorporates these points. 1 aThompson, N A uhttp://mail.iacat.org/content/item-selection-computerized-classification-testing00517nas a2200145 4500008004100000245008100041210006900122300000900191490000600200100001700206700001200223700001500235700001400250856010700264 2009 eng d00aItem selection rules in computerized adaptive testing: Accuracy and security0 aItem selection rules in computerized adaptive testing Accuracy a a7-170 v51 aBarrada, J R1 aOlea, J1 aPonsoda, V1 aAbad, F J uhttp://mail.iacat.org/content/item-selection-rules-computerized-adaptive-testing-accuracy-and-security00461nas a2200109 4500008004100000245005600041210005300097260009700150100001300247700001300260856007800273 2009 eng d00aItem selection with biased-coin up-and-down designs0 aItem selection with biasedcoin upanddown designs aD. J. Weiss (Ed.), Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing.1 aSheng, Y1 aSheng, Z uhttp://mail.iacat.org/content/item-selection-biased-coin-and-down-designs00489nas a2200121 4500008004100000245009800041210006900139300001100208490001000219100001200229700001300241856011300254 2009 eng d00aI've fallen and I can't get up: can high-ability students recover from early mistakes in CAT?0 aIve fallen and I cant get up can highability students recover fr a83-1010 v33(2)1 aRulison1 aLoken, E uhttp://mail.iacat.org/content/ive-fallen-and-i-cant-get-can-high-ability-students-recover-early-mistakes-cat01482nas a2200133 4500008003900000245009800039210006900137300001100206490000700217520103400224100002201258700001601280856005201296 2009 d00aI've Fallen and I Can't Get Up: Can High-Ability Students Recover From Early Mistakes in CAT?0 aIve Fallen and I Cant Get Up Can HighAbility Students Recover Fr a83-1010 v333 a

A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimate initially drops and then ascends continuously until the test ends, suggesting that the true ability may be higher than implied by the final estimate. This study explains why this asymmetry occurs and shows that early mistakes by high-ability students can lead to considerable underestimation, even in tests with 45 items. The opposite response pattern, where low-ability students start with lucky guesses, leads to much less bias. The authors show that using Barton and Lord's four-parameter model (4PM) and a less informative prior can lower bias and root mean square error (RMSE) for high-ability students with a poor start, as the CAT algorithm ascends more quickly after initial underperformance. Results also show that the 4PM slightly outperforms a CAT in which less discriminating items are initially used. The practical implications and relevance for psychological measurement more generally are discussed.

1 aRulison, Kelly, L1 aLoken, Eric uhttp://apm.sagepub.com/content/33/2/83.abstract01482nas a2200133 4500008003900000245009800039210006900137300001100206490000700217520103400224100002201258700001601280856005201296 2009 d00aI've Fallen and I Can't Get Up: Can High-Ability Students Recover From Early Mistakes in CAT?0 aIve Fallen and I Cant Get Up Can HighAbility Students Recover Fr a83-1010 v333 a

A difficult result to interpret in Computerized Adaptive Tests (CATs) occurs when an ability estimate initially drops and then ascends continuously until the test ends, suggesting that the true ability may be higher than implied by the final estimate. This study explains why this asymmetry occurs and shows that early mistakes by high-ability students can lead to considerable underestimation, even in tests with 45 items. The opposite response pattern, where low-ability students start with lucky guesses, leads to much less bias. The authors show that using Barton and Lord's four-parameter model (4PM) and a less informative prior can lower bias and root mean square error (RMSE) for high-ability students with a poor start, as the CAT algorithm ascends more quickly after initial underperformance. Results also show that the 4PM slightly outperforms a CAT in which less discriminating items are initially used. The practical implications and relevance for psychological measurement more generally are discussed.

1 aRulison, Kelly, L1 aLoken, Eric uhttp://apm.sagepub.com/content/33/2/83.abstract00505nas a2200121 4500008004100000245009900041210006900140300001200209490001100221100001900232700001600251856011600267 2008 eng d00aICAT: An adaptive testing procedure for the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure for the identification of idi a40–480 v216(1)1 aKingsbury, G G1 aHouser, R L uhttp://mail.iacat.org/content/icat-adaptive-testing-procedure-identification-idiosyncratic-knowledge-patterns-002195nas a2200145 4500008004100000245009900041210006900140300001000209490000800219520163900227653003401866100001901900700001601919856011401935 2008 eng d00aICAT: An adaptive testing procedure for the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure for the identification of idi a40-480 v2163 a

Traditional adaptive tests provide an efficient method for estimating student achievements levels, by adjusting the characteristicsof the test questions to match the performance of each student. These traditional adaptive tests are not designed to identify diosyncraticknowledge patterns. As students move through their education, they learn content in any number of different ways related to their learning style and cognitive development. This may result in a student having different achievement levels from one content area to another within a domain of content. This study investigates whether such idiosyncratic knowledge patterns exist. It discusses the differences between idiosyncratic knowledge patterns and multidimensionality. Finally, it proposes an adaptive testing procedure that can be used to identify a student’s areas of strength and weakness more efficiently than current adaptive testing approaches. The findings of the study indicate that a fairly large number of students may have test results that are influenced by their idiosyncratic knowledge patterns. The findings suggest that these patterns persist across time for a large number of students, and that the differences in student performance between content areas within a subject domain are large enough to allow them to be useful in instruction. Given the existence of idiosyncratic patterns of knowledge, the proposed testing procedure may enable us to provide more useful information to teachers. It should also allow us to differentiate between idiosyncratic patterns or knowledge, and important mutidimensionality in the testing data.

10acomputerized adaptive testing1 aKingsbury, G G1 aHouser, R L uhttp://mail.iacat.org/content/icat-adaptive-testing-procedure-identification-idiosyncratic-knowledge-patterns01189nas a2200157 4500008004500000245009300045210006900138300001200207490000600219520062800225100001600853700001900869700001400888700001500902856011400917 2008 Engldsh 00aImpact of altering randomization intervals on precision of measurement and item exposure0 aImpact of altering randomization intervals on precision of measu a160-1670 v93 a

This paper reports on the use of simulation when a randomization procedure is used to control item exposure in a computerized adaptive test for certification. We present a method to determine the optimum width of the interval from which items are selected and we report on the impact of relaxing the interval width on measurement precision and item exposure. Results indicate that, if the item bank is well targeted, it may be possible to widen the randomization interval and thus reduce item exposure, without seriously impacting the error of measure for test takers whose ability estimate is near the pass point.

1 aMuckle, T J1 aBergstrom, B A1 aBecker, K1 aStahl, J A uhttp://mail.iacat.org/content/impact-altering-randomization-intervals-precision-measurement-and-item-exposure00469nas a2200121 4500008003900000245011200039210006900151300001200220490000600232100002500238700001900263856006500282 2008 d00aImplementing Sympson-Hetter Item-Exposure Control in a Shadow-Test Approach to Constrained Adaptive Testing0 aImplementing SympsonHetter ItemExposure Control in a ShadowTest  a272-2890 v81 aVeldkamp, Bernard, P1 aLinden, Wim, J uhttp://www.tandfonline.com/doi/abs/10.1080/1530505080226223300547nas a2200145 4500008004100000245009900041210006900140300001200209490000700221100001700228700001200245700001500257700001400272856011500286 2008 eng d00aIncorporating randomness in the Fisher information for improving item-exposure control in CATs0 aIncorporating randomness in the Fisher information for improving a493-5130 v611 aBarrada, J R1 aOlea, J1 aPonsoda, V1 aAbad, F J uhttp://mail.iacat.org/content/incorporating-randomness-fisher-information-improving-item-exposure-control-cats03057nas a2200205 4500008004100000020002700041245012200068210006900190250001500259260001100274300000800285490000600293520234600299100001502645700001402660700001402674700002102688700001502709856012702724 2008 Eng d a1471-2474 (Electronic)00aAn initial application of computerized adaptive testing (CAT) for measuring disability in patients with low back pain0 ainitial application of computerized adaptive testing CAT for mea a2008/12/20 cDec 18 a1660 v93 aABSTRACT: BACKGROUND: Recent approaches to outcome measurement involving Computerized Adaptive Testing (CAT) offer an approach for measuring disability in low back pain (LBP) in a way that can reduce the burden upon patient and professional. The aim of this study was to explore the potential of CAT in LBP for measuring disability as defined in the International Classification of Functioning, Disability and Health (ICF) which includes impairments, activity limitation, and participation restriction. METHODS: 266 patients with low back pain answered questions from a range of widely used questionnaires. An exploratory factor analysis (EFA) was used to identify disability dimensions which were then subjected to Rasch analysis. Reliability was tested by internal consistency and person separation index (PSI). Discriminant validity of disability levels were evaluated by Spearman correlation coefficient (r), intraclass correlation coefficient [ICC(2,1)] and the Bland-Altman approach. A CAT was developed for each dimension, and the results checked against simulated and real applications from a further 133 patients. RESULTS: Factor analytic techniques identified two dimensions named "body functions" and "activity-participation". After deletion of some items for failure to fit the Rasch model, the remaining items were mostly free of Differential Item Functioning (DIF) for age and gender. Reliability exceeded 0.90 for both dimensions. The disability levels generated using all items and those obtained from the real CAT application were highly correlated (i.e. >0.97 for both dimensions). On average, 19 and 14 items were needed to estimate the precise disability levels using the initial CAT for the first and second dimension. However, a marginal increase in the standard error of the estimate across successive iterations substantially reduced the number of items required to make an estimate. CONCLUSIONS: Using a combination approach of EFA and Rasch analysis this study has shown that it is possible to calibrate items onto a single metric in a way that can be used to provide the basis of a CAT application. Thus there is an opportunity to obtain a wide variety of information to evaluate the biopsychosocial model in its more complex forms, without necessarily increasing the burden of information collection for patients.1 aElhan, A H1 aOztuna, D1 aKutlay, S1 aKucukdeveci, A A1 aTennant, A uhttp://mail.iacat.org/content/initial-application-computerized-adaptive-testing-cat-measuring-disability-patients-low-back00463nas a2200121 4500008004100000245008400041210006900125300000900194490000700203100001300210700001400223856010400237 2008 eng d00aInvestigating item exposure control on the fly in computerized adaptive testing0 aInvestigating item exposure control on the fly in computerized a a1-320 v551 aWu, M -L1 aChen, S-Y uhttp://mail.iacat.org/content/investigating-item-exposure-control-fly-computerized-adaptive-testing00442nas a2200121 4500008004100000245007200041210006900113300001200182490000700194100000800201700001400209856009700223 2008 eng d00aItem exposure control in a-stratified computerized adaptive testing0 aItem exposure control in astratified computerized adaptive testi a793-8110 v551 aJhu1 aChen, S-Y uhttp://mail.iacat.org/content/item-exposure-control-stratified-computerized-adaptive-testing00576nas a2200109 4500008004100000245010400041210006900145260009700214100001900311700001600330856012000346 2007 eng d00aICAT: An adaptive testing procedure to allow the identification of idiosyncratic knowledge patterns0 aICAT An adaptive testing procedure to allow the identification o aD. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aKingsbury, G G1 aHouser, R L uhttp://mail.iacat.org/content/icat-adaptive-testing-procedure-allow-identification-idiosyncratic-knowledge-patterns00522nas a2200097 4500008004100000245008500041210007000126260009700196100001600293856011500309 2007 eng d00aImplementing the Graduate Management Admission Test® computerized adaptive test0 aImplementing the Graduate Management Admission Test® computerize aD. J. Weiss (Ed.), Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aRudner, L M uhttp://mail.iacat.org/content/implementing-graduate-management-admission-test%C2%AE-computerized-adaptive-test02876nas a2200313 4500008004100000020002200041245010100063210006900164250001500233260000800248300001200256490000700268520179500275653005102070653002002121653003702141653002602178653001902204653001102223653003002234653004602264653003502310653002802345653001302373100002102386700001702407700001502424856012302439 2007 eng d a0315-162X (Print)00aImproving patient reported outcomes using item response theory and computerized adaptive testing0 aImproving patient reported outcomes using item response theory a a2007/06/07 cJun a1426-310 v343 aOBJECTIVE: Patient reported outcomes (PRO) are considered central outcome measures for both clinical trials and observational studies in rheumatology. More sophisticated statistical models, including item response theory (IRT) and computerized adaptive testing (CAT), will enable critical evaluation and reconstruction of currently utilized PRO instruments to improve measurement precision while reducing item burden on the individual patient. METHODS: We developed a domain hierarchy encompassing the latent trait of physical function/disability from the more general to most specific. Items collected from 165 English-language instruments were evaluated by a structured process including trained raters, modified Delphi expert consensus, and then patient evaluation. Each item in the refined data bank will undergo extensive analysis using IRT to evaluate response functions and measurement precision. CAT will allow for real-time questionnaires of potentially smaller numbers of questions tailored directly to each individual's level of physical function. RESULTS: Physical function/disability domain comprises 4 subdomains: upper extremity, trunk, lower extremity, and complex activities. Expert and patient review led to consensus favoring use of present-tense "capability" questions using a 4- or 5-item Likert response construct over past-tense "performance"items. Floor and ceiling effects, attribution of disability, and standardization of response categories were also addressed. CONCLUSION: By applying statistical techniques of IRT through use of CAT, existing PRO instruments may be improved to reduce questionnaire burden on the individual patients while increasing measurement precision that may ultimately lead to reduced sample size requirements for costly clinical trials.10a*Rheumatic Diseases/physiopathology/psychology10aClinical Trials10aData Interpretation, Statistical10aDisability Evaluation10aHealth Surveys10aHumans10aInternational Cooperation10aOutcome Assessment (Health Care)/*methods10aPatient Participation/*methods10aResearch Design/*trends10aSoftware1 aChakravarty, E F1 aBjorner, J B1 aFries, J F uhttp://mail.iacat.org/content/improving-patient-reported-outcomes-using-item-response-theory-and-computerized-adaptive02413nas a2200361 4500008004500000020001400045245011100059210006900170300001200239490000700251520135900258653001601617653002001633653001301653653002401666653002501690653001101715653001401726653001301740653001801753653002701771653001001798653001101808100001501819700001201834700001601846700001201862700001601874700001301890700001301903700001401916856012101930 2007 Engldsh  a1057-924900aThe initial development of an item bank to assess and screen for psychological distress in cancer patients0 ainitial development of an item bank to assess and screen for psy a724-7320 v163 aPsychological distress is a common problem among cancer patients. Despite the large number of instruments that have been developed to assess distress, their utility remains disappointing. This study aimed to use Rasch models to develop an item-bank which would provide the basis for better means of assessing psychological distress in cancer patients. An item bank was developed from eight psychological distress questionnaires using Rasch analysis to link common items. Items from the questionnaires were added iteratively with common items as anchor points and misfitting items (infit mean square > 1.3) removed, and unidimensionality assessed. A total of 4914 patients completed the questionnaires providing an initial pool of 83 items. Twenty items were removed resulting in a final pool of 63 items. Good fit was demonstrated and no additional factor structure was evident from the residuals. However, there was little overlap between item locations and person measures, since items mainly targeted higher levels of distress. The Rasch analysis allowed items to be pooled and generated a unidimensional instrument for measuring psychological distress in cancer patients. Additional items are required to more accurately assess patients across the whole continuum of psychological distress. (PsycINFO Database Record (c) 2007 APA ) (journal abstract)10a3293 Cancer10acancer patients10aDistress10ainitial development10aItem Response Theory10aModels10aNeoplasms10aPatients10aPsychological10apsychological distress10aRasch10aStress1 aSmith, A B1 aRush, R1 aVelikova, G1 aWall, L1 aWright, E P1 aStark, D1 aSelby, P1 aSharpe, M uhttp://mail.iacat.org/content/initial-development-item-bank-assess-and-screen-psychological-distress-cancer-patients00515nas a2200109 4500008004100000245007300041210006900114260010000183100001600283700001300299856009300312 2007 eng d00aInvestigating CAT designs to achieve comparability with a paper test0 aInvestigating CAT designs to achieve comparability with a paper  aIn D. J. Weiss (Ed.). Proceedings of the 2007 GMAC Conference on Computerized Adaptive Testing.1 aThompson, T1 aWay, W D uhttp://mail.iacat.org/content/investigating-cat-designs-achieve-comparability-paper-test03105nas a2200445 4500008004100000020002200041245007100063210006900134250001500203300001200218490000700230520183100237653003802068653001902106653002102125653002002146653001402166653001102180653003002191653001102221653000902232653002502241653004602266653001802312653002602330100001302356700001402369700001702383700001302400700001502413700001502428700001702443700001402460700001802474700002302492700001602515700001602531700001502547856009702562 2007 eng d a0962-9343 (Print)00aIRT health outcomes data analysis project: an overview and summary0 aIRT health outcomes data analysis project an overview and summar a2007/03/14 a121-1320 v163 aBACKGROUND: In June 2004, the National Cancer Institute and the Drug Information Association co-sponsored the conference, "Improving the Measurement of Health Outcomes through the Applications of Item Response Theory (IRT) Modeling: Exploration of Item Banks and Computer-Adaptive Assessment." A component of the conference was presentation of a psychometric and content analysis of a secondary dataset. OBJECTIVES: A thorough psychometric and content analysis was conducted of two primary domains within a cancer health-related quality of life (HRQOL) dataset. RESEARCH DESIGN: HRQOL scales were evaluated using factor analysis for categorical data, IRT modeling, and differential item functioning analyses. In addition, computerized adaptive administration of HRQOL item banks was simulated, and various IRT models were applied and compared. SUBJECTS: The original data were collected as part of the NCI-funded Quality of Life Evaluation in Oncology (Q-Score) Project. A total of 1,714 patients with cancer or HIV/AIDS were recruited from 5 clinical sites. MEASURES: Items from 4 HRQOL instruments were evaluated: Cancer Rehabilitation Evaluation System-Short Form, European Organization for Research and Treatment of Cancer Quality of Life Questionnaire, Functional Assessment of Cancer Therapy and Medical Outcomes Study Short-Form Health Survey. RESULTS AND CONCLUSIONS: Four lessons learned from the project are discussed: the importance of good developmental item banks, the ambiguity of model fit results, the limits of our knowledge regarding the practical implications of model misfit, and the importance in the measurement of HRQOL of construct definition. With respect to these lessons, areas for future research are suggested. The feasibility of developing item banks for broad definitions of health is discussed.10a*Data Interpretation, Statistical10a*Health Status10a*Quality of Life10a*Questionnaires10a*Software10aFemale10aHIV Infections/psychology10aHumans10aMale10aNeoplasms/psychology10aOutcome Assessment (Health Care)/*methods10aPsychometrics10aStress, Psychological1 aCook, KF1 aTeal, C R1 aBjorner, J B1 aCella, D1 aChang, C-H1 aCrane, P K1 aGibbons, L E1 aHays, R D1 aMcHorney, C A1 aOcepek-Welikson, K1 aRaczek, A E1 aTeresi, J A1 aReeve, B B uhttp://mail.iacat.org/content/irt-health-outcomes-data-analysis-project-overview-and-summary00387nas a2200097 4500008004100000245005800041210005800099260002700157100001800184856008700202 2007 eng d00aItem selection in computerized classification testing0 aItem selection in computerized classification testing aUniversity of Nebraska1 aThompson, N A uhttp://mail.iacat.org/content/item-selection-computerized-classification-testing-000333nas a2200109 4500008003900000245004200039210003900081300001200120490000700132100001800139856006600157 2006 d00aAn Introduction to Multistage Testing0 aIntroduction to Multistage Testing a185-1870 v191 aMead, Alan, D uhttp://www.tandfonline.com/doi/abs/10.1207/s15324818ame1903_102187nas a2200181 4500008004100000245009900041210006900140260000800209300001400217490000700231520157400238100001401812700001301826700001401839700001601853700001301869856012301882 2006 eng d00aItem banks and their potential applications to health status assessment in diverse populations0 aItem banks and their potential applications to health status ass cNov aS189-S1970 v443 aIn the context of an ethnically diverse, aging society, attention is increasingly turning to health-related quality of life measurement to evaluate healthcare and treatment options for chronic diseases. When evaluating and treating symptoms and concerns such as fatigue, pain, or physical function, reliable and accurate assessment is a priority. Modern psychometric methods have enabled us to move from long, static tests that provide inefficient and often inaccurate assessment of individual patients, to computerized adaptive tests (CATs) that can precisely measure individuals on health domains of interest. These modern methods, collectively referred to as item response theory (IRT), can produce calibrated "item banks" from larger pools of questions. From these banks, CATs can be conducted on individuals to produce their scores on selected domains. Item banks allow for comparison of patients across different question sets because the patient's score is expressed on a common scale. Other advantages of using item banks include flexibility in terms of the degree of precision desired; interval measurement properties under most circumstances; realistic capability for accurate individual assessment over time (using CAT); and measurement equivalence across different patient populations. This work summarizes the process used in the creation and evaluation of item banks and reviews their potential contributions and limitations regarding outcome assessment and patient care, particularly when they are applied across people of different cultural backgrounds.1 aHahn, E A1 aCella, D1 aBode, R K1 aGershon, RC1 aLai, J S uhttp://mail.iacat.org/content/item-banks-and-their-potential-applications-health-status-assessment-diverse-populations03384nas a2200205 4500008004100000020002200041245009700063210006900160260002500229300001200254490000700266520266000273653003402933653002802967100001502995700001903010700001703029700001403046856011803060 2006 eng d a0439-755X (Print)00a[Item Selection Strategies of Computerized Adaptive Testing based on Graded Response Model.]0 aItem Selection Strategies of Computerized Adaptive Testing based bScience Press: China a461-4670 v383 aItem selection strategy (ISS) is an important component of Computerized Adaptive Testing (CAT). Its performance directly affects the security, efficiency and precision of the test. Thus, ISS becomes one of the central issues in CATs based on the Graded Response Model (GRM). It is well known that the goal of IIS is to administer the next unused item remaining in the item bank that best fits the examinees current ability estimate. In dichotomous IRT models, every item has only one difficulty parameter and the item whose difficulty matches the examinee's current ability estimate is considered to be the best fitting item. However, in GRM, each item has more than two ordered categories and has no single value to represent the item difficulty. Consequently, some researchers have used to employ the average or the median difficulty value across categories as the difficulty estimate for the item. Using the average value and the median value in effect introduced two corresponding ISSs. In this study, we used computer simulation compare four ISSs based on GRM. We also discussed the effect of "shadow pool" on the uniformity of pool usage as well as the influence of different item parameter distributions and different ability estimation methods on the evaluation criteria of CAT. In the simulation process, Monte Carlo method was adopted to simulate the entire CAT process; 1,000 examinees drawn from standard normal distribution and four 1,000-sized item pools of different item parameter distributions were also simulated. The assumption of the simulation is that a polytomous item is comprised of six ordered categories. In addition, ability estimates were derived using two methods. They were expected a posteriori Bayesian (EAP) and maximum likelihood estimation (MLE). In MLE, the Newton-Raphson iteration method and the Fisher Score iteration method were employed, respectively, to solve the likelihood equation. Moreover, the CAT process was simulated with each examinee 30 times to eliminate random error. The IISs were evaluated by four indices usually used in CAT from four aspects--the accuracy of ability estimation, the stability of IIS, the usage of item pool, and the test efficiency. Simulation results showed adequate evaluation of the ISS that matched the estimate of an examinee's current trait level with the difficulty values across categories. Setting "shadow pool" in ISS was able to improve the uniformity of pool utilization. Finally, different distributions of the item parameter and different ability estimation methods affected the evaluation indices of CAT. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10acomputerized adaptive testing10aitem selection strategy1 aPing, Chen1 aShuliang, Ding1 aHaijing, Lin1 aJie, Zhou uhttp://mail.iacat.org/content/item-selection-strategies-computerized-adaptive-testing-based-graded-response-model00453nas a2200121 4500008004100000245006700041210006700108260002100175100001000196700001300206700001900219856009300238 2005 eng d00aIdentifying practical indices for enhancing item pool security0 aIdentifying practical indices for enhancing item pool security aMontreal, Canada1 aYi, Q1 aZhang, J1 aChang, Hua-Hua uhttp://mail.iacat.org/content/identifying-practical-indices-enhancing-item-pool-security00650nas a2200109 4500008004100000245010000041210006900141260017200210100001800382700001900400856012100419 2005 eng d00aAn implemented theoretical framework for a common European foreign language adaptive assessment0 aimplemented theoretical framework for a common European foreign  aProceedings ICODL 2005, 3rd ternational Conference on Open and Distance Learning 'Applications of Pedagogy and Technology',339-350,Greek Open University, Patra, Greece1 aGiouroglou, H1 aEconomides, AA uhttp://mail.iacat.org/content/implemented-theoretical-framework-common-european-foreign-language-adaptive-assessment00554nas a2200109 4500008004100000245010300041210006900144260006800213100002300281700001900304856012100323 2005 eng d00aImplementing content constraints in alpha-stratified adaptive testing using a shadow test approach0 aImplementing content constraints in alphastratified adaptive tes aLaw School Admission Council, Computerized Testing Report 01-091 avan der Linden, WJ1 aChang, Hua-Hua uhttp://mail.iacat.org/content/implementing-content-constraints-alpha-stratified-adaptive-testing-using-shadow-test-002242nas a2200217 4500008004100000020002200041245014200063210006900205260004100274300001200315490000700327520142600334653001401760653003401774653002301808653001601831653002701847100001201874700001701886856012101903 2005 eng d a0022-0655 (Print)00aIncreasing the homogeneity of CAT's item-exposure rates by minimizing or maximizing varied target functions while assembling shadow tests0 aIncreasing the homogeneity of CATs itemexposure rates by minimiz bBlackwell Publishing: United Kingdom a245-2690 v423 aA computerized adaptive testing (CAT) algorithm that has the potential to increase the homogeneity of CATs item-exposure rates without significantly sacrificing the precision of ability estimates was proposed and assessed in the shadow-test (van der Linden & Reese, 1998) CAT context. This CAT algorithm was formed by a combination of maximizing or minimizing varied target functions while assembling shadow tests. There were four target functions to be separately used in the first, second, third, and fourth quarter test of CAT. The elements to be used in the four functions were associated with (a) a random number assigned to each item, (b) the absolute difference between an examinee's current ability estimate and an item difficulty, (c) the absolute difference between an examinee's current ability estimate and an optimum item difficulty, and (d) item information. The results indicated that this combined CAT fully utilized all the items in the pool, reduced the maximum exposure rates, and achieved more homogeneous exposure rates. Moreover, its precision in recovering ability estimates was similar to that of the maximum item-information method. The combined CAT method resulted in the best overall results compared with the other individual CAT item-selection methods. The findings from the combined CAT are encouraging. Future uses are discussed. (PsycINFO Database Record (c) 2007 APA, all rights reserved)10aalgorithm10acomputerized adaptive testing10aitem exposure rate10ashadow test10avaried target function1 aLi, Y H1 aSchafer, W D uhttp://mail.iacat.org/content/increasing-homogeneity-cats-item-exposure-rates-minimizing-or-maximizing-varied-target02021nas a2200193 4500008004100000245009300041210006900134300001200203490000700215520136400222653001501586653002401601653001101625653002201636100001801658700001801676700001901694856011401713 2005 eng d00aInfeasibility in automated test assembly models: A comparison study of different methods0 aInfeasibility in automated test assembly models A comparison stu a223-2430 v423 aSeveral techniques exist to automatically put together a test meeting a number of specifications. In an item bank, the items are stored with their characteristics. A test is constructed by selecting a set of items that fulfills the specifications set by the test assembler. Test assembly problems are often formulated in terms of a model consisting of restrictions and an objective to be maximized or minimized. A problem arises when it is impossible to construct a test from the item pool that meets all specifications, that is, when the model is not feasible. Several methods exist to handle these infeasibility problems. In this article, test assembly models resulting from two practical testing programs were reconstructed to be infeasible. These models were analyzed using methods that forced a solution (Goal Programming, Multiple-Goal Programming, Greedy Heuristic), that analyzed the causes (Relaxed and Ordered Deletion Algorithm (RODA), Integer Randomized Deletion Algorithm (IRDA), Set Covering (SC), and Item Sampling), or that analyzed the causes and used this information to force a solution (Irreducible Infeasible Set-Solver). Specialized methods such as the IRDA and the Irreducible Infeasible Set-Solver performed best. Recommendations about the use of different methods are given. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAlgorithms10aItem Content (Test)10aModels10aTest Construction1 aHuitzing, H A1 aVeldkamp, B P1 aVerschoor, A J uhttp://mail.iacat.org/content/infeasibility-automated-test-assembly-models-comparison-study-different-methods02444nas a2200373 4500008004100000020004100041245008200082210006900164250001500233260000800248300001000256490000700266520136700273653001001640653000901650653002201659653003301681653003301714653001101747653001101758653000901769653001601778653004001794653001801834653001901852100001301871700001301884700001401897700001201911700001701923700001601940700001501956856009901971 2005 eng d a0895-4356 (Print)0895-4356 (Linking)00aAn item bank was created to improve the measurement of cancer-related fatigue0 aitem bank was created to improve the measurement of cancerrelate a2005/02/01 cFeb a190-70 v583 aOBJECTIVE: Cancer-related fatigue (CRF) is one of the most common unrelieved symptoms experienced by patients. CRF is underrecognized and undertreated due to a lack of clinically sensitive instruments that integrate easily into clinics. Modern computerized adaptive testing (CAT) can overcome these obstacles by enabling precise assessment of fatigue without requiring the administration of a large number of questions. A working item bank is essential for development of a CAT platform. The present report describes the building of an operational item bank for use in clinical settings with the ultimate goal of improving CRF identification and treatment. STUDY DESIGN AND SETTING: The sample included 301 cancer patients. Psychometric properties of items were examined by using Rasch analysis, an Item Response Theory (IRT) model. RESULTS AND CONCLUSION: The final bank includes 72 items. These 72 unidimensional items explained 57.5% of the variance, based on factor analysis results. Excellent internal consistency (alpha=0.99) and acceptable item-total correlation were found (range: 0.51-0.85). The 72 items covered a reasonable range of the fatigue continuum. No significant ceiling effects, floor effects, or gaps were found. A sample short form was created for demonstration purposes. The resulting bank is amenable to the development of a CAT platform.10aAdult10aAged10aAged, 80 and over10aFactor Analysis, Statistical10aFatigue/*etiology/psychology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/*complications/psychology10aPsychometrics10aQuestionnaires1 aLai, J-S1 aCella, D1 aDineen, K1 aBode, R1 aVon Roenn, J1 aGershon, RC1 aShevrin, D uhttp://mail.iacat.org/content/item-bank-was-created-improve-measurement-cancer-related-fatigue01316nas a2200229 4500008004100000020002200041245007700063210006900140260002500209300001200234490000700246520057900253653002700832653003000859653002500889100001100914700001600925700001500941700001300956700001500969856010200984 2005 eng d a0439-755X (Print)00a[Item characteristic curve equating under graded response models in IRT]0 aItem characteristic curve equating under graded response models  bScience Press: China a832-8380 v373 aIn one of the largest qualificatory tests--economist test, to guarantee the comparability among different years, construct item bank and prepare for computerized adaptive testing, item characteristic curve equating and anchor test equating design under graded models in IRT are used, which have realized the item and ability parameter equating of test data in five years and succeeded in establishing an item bank. Based on it, cut scores of different years are compared by equating and provide demonstrational gist to constitute the eligibility standard of economist test. 10agraded response models10aitem characteristic curve10aItem Response Theory1 aJun, Z1 aDongming, O1 aShuyuan, X1 aHaiqi, D1 aShuqing, Q uhttp://mail.iacat.org/content/item-characteristic-curve-equating-under-graded-response-models-irt00560nas a2200145 4500008003900000245011100039210006900150300001000219490000700229100001400236700001400250700001800264700001700282856011500299 2005 d00aItem response theory in computer adaptive testing: implications for outcomes measurement in rehabilitation0 aItem response theory in computer adaptive testing implications f a71-780 v501 aWare, J E1 aGandek, B1 aSinclair, S J1 aBjorner, J B uhttp://mail.iacat.org/content/item-response-theory-computer-adaptive-testing-implications-outcomes-measurement01744nas a2200229 4500008004100000245008300041210006900124300001100193490000700204520103000211653003401241100001301275700001401288700001501302700001701317700001501334700001501349700001401364700001301378700001301391856011001404 2005 eng d00aAn item response theory-based pain item bank can enhance measurement precision0 aitem response theorybased pain item bank can enhance measurement a278-880 v303 aCancer-related pain is often under-recognized and undertreated. This is partly due to the lack of appropriate assessments, which need to be comprehensive and precise yet easily integrated into clinics. Computerized adaptive testing (CAT) can enable precise-yet-brief assessments by only selecting the most informative items from a calibrated item bank. The purpose of this study was to create such a bank. The sample included 400 cancer patients who were asked to complete 61 pain-related items. Data were analyzed using factor analysis and the Rasch model. The final bank consisted of 43 items which satisfied the measurement requirement of factor analysis and the Rasch model, demonstrated high internal consistency and reasonable item-total correlations, and discriminated patients with differing degrees of pain. We conclude that this bank demonstrates good psychometric properties, is sensitive to pain reported by patients, and can be used as the foundation for a CAT pain-testing platform for use in clinical practice.10acomputerized adaptive testing1 aLai, J-S1 aDineen, K1 aReeve, B B1 aVon Roenn, J1 aShervin, D1 aMcGuire, M1 aBode, R K1 aPaice, J1 aCella, D uhttp://mail.iacat.org/content/item-response-theory-based-pain-item-bank-can-enhance-measurement-precision01470nas a2200133 4500008003900000245013600039210006900175300000900244490000700253520098400260100001601244700002501260856005101285 2004 d00aImpact of Test Design, Item Quality, and Item Bank Size on the Psychometric Properties of Computer-Based Credentialing Examinations0 aImpact of Test Design Item Quality and Item Bank Size on the Psy a5-210 v643 a

Computer-based testing by credentialing agencies has become common; however, selecting a test design is difficult because several good ones are available—parallel forms, computer adaptive (CAT), and multistage (MST). In this study, three computerbased test designs under some common examination conditions were investigated. Item bank size and item quality had a practically significant impact on decision consistency and accuracy. Even in nearly ideal situations, the choice of test design was not a factor in the results. Two conclusions follow from the findings: (a) More time and resources should be committed to expanding the size and quality of item banks, and (b) designs that individualize an exam administration such as MST and CAT may not be helpful when the primary purpose of the examination is to make pass-fail decisions and conditions are present for using parallel forms with a target information function that can be centered on the passing score.

1 aXing, Dehui1 aHambleton, Ronald, K uhttp://epm.sagepub.com/content/64/1/5.abstract01192nas a2200133 4500008003900000245009600039210006900135300001200204490000700216520074500223100002000968700001700988856005301005 2004 d00aImplementation and Measurement Efficiency of Multidimensional Computerized Adaptive Testing0 aImplementation and Measurement Efficiency of Multidimensional Co a295-3160 v283 a

Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random administration. The results showed that the higher the correlation between latent traits, the more latent traits there were, and the more scoring levels there were in the items, the more efficient MAT was than the other two procedures. For tests containing multidimensional items, only MAT is applicable, whereas unidimensional adaptive testing is not. Issues in implementing MAT are discussed.

1 aWang, Wen-Chung1 aChen, Po-Hsi uhttp://apm.sagepub.com/content/28/5/295.abstract00502nas a2200109 4500008004100000245010500041210006900146260001700215100001700232700001800249856012500267 2004 eng d00aInvestigating the effects of selected multi-stage test design alternatives on credentialing outcomes0 aInvestigating the effects of selected multistage test design alt aSan Diego CA1 aZenisky, A L1 aHambleton, RK uhttp://mail.iacat.org/content/investigating-effects-selected-multi-stage-test-design-alternatives-credentialing-outcomes00710nas a2200157 4500008004100000245013900041210006900180260003200249653003400281653004000315653004100355100001200396700001200408700001200420856012000432 2004 eng d00aAn investigation of two combination procedures of SPRT for three-category classification decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat aSan Antonio, Texasc04/200410acomputerized adaptive testing10aComputerized classification testing10asequential probability ratio testing1 aJiao, H1 aWang, S1 aLau, CA uhttp://mail.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-classification-decisions00614nas a2200121 4500008004100000245012400041210006900165260010500234100001200339700001200351700001100363856011800374 2004 eng d00aAn investigation of two combination procedures of SPRT for three-category decisions in computerized classification test0 ainvestigation of two combination procedures of SPRT for threecat aPaper presented at the annual meeting of the American Educational Research Association, San Diego CA1 aJiao, H1 aWang, S1 aLau, A uhttp://mail.iacat.org/content/investigation-two-combination-procedures-sprt-three-category-decisions-computerized00391nas a2200121 4500008004100000245004800041210004800089260001700137100001200154700001500166700001500181856007300196 2004 eng d00aItem parameter recovery with adaptive tests0 aItem parameter recovery with adaptive tests aSan Diego CA1 aDo, B-R1 aChuah, S C1 aDrasgow, F uhttp://mail.iacat.org/content/item-parameter-recovery-adaptive-tests00505nas a2200109 4500008004100000245010400041210006900145260001500214100001800229700002300247856012500270 2003 eng d00aImplementing an alternative to Sympson-Hetter item-exposure control in constrained adaptive testing0 aImplementing an alternative to SympsonHetter itemexposure contro aChicago IL1 aVeldkamp, B P1 avan der Linden, WJ uhttp://mail.iacat.org/content/implementing-alternative-sympson-hetter-item-exposure-control-constrained-adaptive-testing00515nas a2200121 4500008004100000245010300041210006900144300001200213490000700225100002300232700001900255856011900274 2003 eng d00aImplementing content constraints in alpha-stratified adaptive testing using a shadow test approach0 aImplementing content constraints in alphastratified adaptive tes a107-1200 v271 avan der Linden, WJ1 aChang, Hua-Hua uhttp://mail.iacat.org/content/implementing-content-constraints-alpha-stratified-adaptive-testing-using-shadow-test00539nas a2200121 4500008004100000245013200041210006900173260001500242100001000257700001200267700001200279856012600291 2003 eng d00aImplementing the a-stratified method with b blocking in computerized adaptive testing with the generalized partial credit model0 aImplementing the astratified method with b blocking in computeri aChicago IL1 aYi, Q1 aWang, T1 aWang, S uhttp://mail.iacat.org/content/implementing-stratified-method-b-blocking-computerized-adaptive-testing-generalized-partial00962nas a2200157 4500008004100000245011200041210006900153300001100222490000700233520035900240653003400599100001500633700001900648700001300667856012400680 2003 eng d00aIncorporation of Content Balancing Requirements in Stratification Designs for Computerized Adaptive Testing0 aIncorporation of Content Balancing Requirements in Stratificatio a257-700 v633 aStudied three stratification designs for computerized adaptive testing in conjunction with three well-developed content balancing methods. Simulation study results show substantial differences in item overlap rate and pool utilization among different methods. Recommends an optimal combination of stratification design and content balancing method. (SLD)10acomputerized adaptive testing1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://mail.iacat.org/content/incorporation-content-balancing-requirements-stratification-designs-computerized-adaptive01586nas a2200145 4500008003900000245011200039210006900151300001200220490000700232520109100239100002101330700001901351700001701370856005301387 2003 d00aIncorporation Of Content Balancing Requirements In Stratification Designs For Computerized Adaptive Testing0 aIncorporation Of Content Balancing Requirements In Stratificatio a257-2700 v633 a

In computerized adaptive testing, the multistage a-stratified design advocates a new philosophy on pool management and item selection in which, contradictory to common practice, less discriminating items are used first. The method is effective in reducing item-overlap rate and enhancing pool utilization. This stratification method has been extended in different ways to deal with the practical issues of content constraints and the positive correlation between item difficulty and discrimination. Nevertheless, these modified designs on their own do not automatically satisfy content requirements. In this study, three stratification designs were examined in conjunction with three well developed content balancing methods. The performance of each of these nine combinational methods was evaluated in terms of their item security, measurement efficiency, and pool utilization. Results showed substantial differences in item-overlap rate and pool utilization among different methods. An optimal combination of stratification design and content balancing method is recommended.

1 aLeung, Chi-Keung1 aChang, Hua-Hua1 aHau, Kit-Tai uhttp://epm.sagepub.com/content/63/2/257.abstract00538nas a2200109 4500008004100000245014400041210006900185260001500254100001200269700001700281856013000298 2003 eng d00aIncreasing the homogeneity of CAT’s item-exposure rates by minimizing or maximizing varied target functions while assembling shadow tests0 aIncreasing the homogeneity of CAT s itemexposure rates by minimi aChicago IL1 aLi, Y H1 aSchafer, W D uhttp://mail.iacat.org/content/increasing-homogeneity-cat%E2%80%99s-item-exposure-rates-minimizing-or-maximizing-varied-target00367nas a2200097 4500008004100000245005500041210005500096260002000151100001600171856008200187 2003 eng d00aInformation theoretic approaches to item selection0 aInformation theoretic approaches to item selection aSardinia, Italy1 aWeissman, A uhttp://mail.iacat.org/content/information-theoretic-approaches-item-selection00378nas a2200097 4500008004100000245006200041210006100103260001500164100002000179856008100199 2003 eng d00aIssues in maintaining scale consistency for the CAT-ASVAB0 aIssues in maintaining scale consistency for the CATASVAB aChicago IL1 aNicewander, W A uhttp://mail.iacat.org/content/issues-maintaining-scale-consistency-cat-asvab02749nas a2200349 4500008004100000245015800041210006900199260000800268300001200276490000700288520160300295653003001898653002001928653001001948653003201958653001101990653001102001653000902012653001602021653002802037653001802065653003702083653004102120653002802161100001302189700001502202700001302217700001502230700001402245700001902259856012102278 2003 eng d00aItem banking to improve, shorten and computerized self-reported fatigue: an illustration of steps to create a core item bank from the FACIT-Fatigue Scale0 aItem banking to improve shorten and computerized selfreported fa cAug a485-5010 v123 aFatigue is a common symptom among cancer patients and the general population. Due to its subjective nature, fatigue has been difficult to effectively and efficiently assess. Modern computerized adaptive testing (CAT) can enable precise assessment of fatigue using a small number of items from a fatigue item bank. CAT enables brief assessment by selecting questions from an item bank that provide the maximum amount of information given a person's previous responses. This article illustrates steps to prepare such an item bank, using 13 items from the Functional Assessment of Chronic Illness Therapy Fatigue Subscale (FACIT-F) as the basis. Samples included 1022 cancer patients and 1010 people from the general population. An Item Response Theory (IRT)-based rating scale model, a polytomous extension of the Rasch dichotomous model was utilized. Nine items demonstrating acceptable psychometric properties were selected and positioned on the fatigue continuum. The fatigue levels measured by these nine items along with their response categories covered 66.8% of the general population and 82.6% of the cancer patients. Although the operational CAT algorithms to handle polytomously scored items are still in progress, we illustrated how CAT may work by using nine core items to measure level of fatigue. Using this illustration, a fatigue measure comparable to its full-length 13-item scale administration was obtained using four items. The resulting item bank can serve as a core to which will be added a psychometrically sound and operational item bank covering the entire fatigue continuum.10a*Health Status Indicators10a*Questionnaires10aAdult10aFatigue/*diagnosis/etiology10aFemale10aHumans10aMale10aMiddle Aged10aNeoplasms/complications10aPsychometrics10aResearch Support, Non-U.S. Gov't10aResearch Support, U.S. Gov't, P.H.S.10aSickness Impact Profile1 aLai, J-S1 aCrane, P K1 aCella, D1 aChang, C-H1 aBode, R K1 aHeinemann, A W uhttp://mail.iacat.org/content/item-banking-improve-shorten-and-computerized-self-reported-fatigue-illustration-steps01748nas a2200217 4500008004100000245008700041210006900128300001200197490000700209520100200216653002101218653003001239653002601269653002501295653002001320653001401340653004901354100001401403700001401417856009901431 2003 eng d00aItem exposure constraints for testlets in the verbal reasoning section of the MCAT0 aItem exposure constraints for testlets in the verbal reasoning s a335-3560 v273 aThe current study examined item exposure control procedures for testlet scored reading passages in the Verbal Reasoning section of the Medical College Admission Test with four computerized adaptive testing (CAT) systems using the partial credit model. The first system used a traditional CAT using maximum information item selection. The second used random item selection to provide a baseline for optimal exposure rates. The third used a variation of Lunz and Stahl's randomization procedure. The fourth used Luecht and Nungester's computerized adaptive sequential testing (CAST) system. A series of simulated fixed-length CATs was run to determine the optimal item length selection procedure. Results indicated that both the randomization procedure and CAST performed well in terms of exposure control and measurement precision, with the CAST system providing the best overall solution when all variables were taken into consideration. (PsycINFO Database Record (c) 2005 APA ) (journal abstract)10aAdaptive Testing10aComputer Assisted Testing10aEntrance Examinations10aItem Response Theory10aRandom Sampling10aReasoning10aVerbal Ability computerized adaptive testing1 aDavis, LL1 aDodd, B G uhttp://mail.iacat.org/content/item-exposure-constraints-testlets-verbal-reasoning-section-mcat00356nas a2200097 4500008004100000245005300041210005300094260001500147100001700162856007900179 2003 eng d00aItem pool design for computerized adaptive tests0 aItem pool design for computerized adaptive tests aChicago IL1 aReckase, M D uhttp://mail.iacat.org/content/item-pool-design-computerized-adaptive-tests00449nas a2200097 4500008004100000245003700041210003700078260015200115100001800267856006600285 2003 eng d00aItem selection in polytomous CAT0 aItem selection in polytomous CAT aH. Yanai, A. Okada, K. Shigemasu, Y Kano, and J. J. Meulman (eds.), New developments in psychometrics (pp. 207-214). Tokyo, Japan: Springer-Verlag.1 aVeldkamp, B P uhttp://mail.iacat.org/content/item-selection-polytomous-cat-000521nas a2200169 4500008004100000245003700041210003700078260004900115300001400164653003400178100001800212700001300230700001700243700001200260700001500272856006400287 2003 eng d00aItem selection in polytomous CAT0 aItem selection in polytomous CAT aTokyo, JapanbPsychometric Society, Springer a207–21410acomputerized adaptive testing1 aVeldkamp, B P1 aOkada, A1 aShigenasu, K1 aKano, Y1 aMeulman, J uhttp://mail.iacat.org/content/item-selection-polytomous-cat00484nas a2200109 4500008004100000245009700041210006900138260001900207100001900226700001300245856011600258 2002 eng d00aIdentify the lower bounds for item sharing and item pooling in computerized adaptive testing0 aIdentify the lower bounds for item sharing and item pooling in c aNew Orleans LA1 aChang, Hua-Hua1 aZhang, J uhttp://mail.iacat.org/content/identify-lower-bounds-item-sharing-and-item-pooling-computerized-adaptive-testing00480nas a2200097 4500008004100000245011200041210006900153260001900222100001800241856012300259 2002 eng d00aImpact of item quality and item bank size on the psychometric quality of computer-based credentialing exams0 aImpact of item quality and item bank size on the psychometric qu aNew Orleans LA1 aHambleton, RK uhttp://mail.iacat.org/content/impact-item-quality-and-item-bank-size-psychometric-quality-computer-based-credentialing00554nas a2200121 4500008004100000245013500041210006900176260001900245100001800264700001400282700001700296856011900313 2002 eng d00aImpact of selected factors on the psychometric quality of credentialing examinations administered with a sequential testlet design0 aImpact of selected factors on the psychometric quality of creden aNew Orleans LA1 aHambleton, RK1 aJodoin, M1 aZenisky, A L uhttp://mail.iacat.org/content/impact-selected-factors-psychometric-quality-credentialing-examinations-administered00518nas a2200109 4500008004100000245012800041210006900169260001600238100001200254700001800266856012400284 2002 eng d00aImpact of test design, item quality and item bank size on the psychometric properties of computer-based credentialing exams0 aImpact of test design item quality and item bank size on the psy aNew Orleans1 aXing, D1 aHambleton, RK uhttp://mail.iacat.org/content/impact-test-design-item-quality-and-item-bank-size-psychometric-properties-computer-based02792nas a2200133 4500008004100000245010200041210006900143300000900212490000700221520226500228653003402493100002002527856011102547 2002 eng d00aThe implications of the use of non-optimal items in a Computer Adaptive Testing (CAT) environment0 aimplications of the use of nonoptimal items in a Computer Adapti a16060 v633 aThis study describes the effects of manipulating item difficulty in a computer adaptive testing (CAT) environment. There are many potential benefits when using CATS as compared to traditional tests. These include increased security, shorter tests, and more precise measurement. According to IRT, the theory underlying CAT, as the computer continually recalculates ability, items that match that current estimate of ability are administered. Such items provide maximum information about examinees during the test. Herein, however, lies a potential problem. These optimal CAT items result in an examinee having only a 50% chance of a correct response. Some examinees may consider such items unduly challenging. Further, when test anxiety is a factor, it is possible that test scores may be negatively affected. This research was undertaken to determine the effects of administering easier CAT items on ability estimation and test length using computer simulations. Also considered was the administration of different numbers of initial items prior to the start of the adaptive portion of the test, using three different levels of measurement precision. Results indicate that regardless of the number of initial items administered, the level of precision employed, or the modifications made to item difficulty, the approximation of estimated ability to true ability is good in all cases. Additionally, the standard deviations of the ability estimates closely approximate the theoretical levels of precision used as stopping rules for the simulated CATs. Since optimal CAT items are not used, each item administered provides less information about examinees than optimal CAT items. This results in longer tests. Fortunately, using easier items that provide up to a 66.4% chance of a correct response results in tests that only modestly increase in length, across levels of precision. For larger standard errors, even easier items (up to a 73.5% chance of a correct response) result in only negligible to modest increases in test length. Examinees who find optimal CAT items difficult or examinees with test anxiety may find CATs that implement easier items enhance the already existing benefits of CAT. (PsycINFO Database Record (c) 2003 APA, all rights reserved).10acomputerized adaptive testing1 aGrodenchik, D J uhttp://mail.iacat.org/content/implications-use-non-optimal-items-computer-adaptive-testing-cat-environment00472nas a2200097 4500008004100000245011200041210006900153260002000222100001000242856012200252 2002 eng d00aIncorporating the Sympson-Hetter exposure control method into the a-stratified method with content blocking0 aIncorporating the SympsonHetter exposure control method into the aNew Orleans, LA1 aYi, Q uhttp://mail.iacat.org/content/incorporating-sympson-hetter-exposure-control-method-stratified-method-content-blocking01218nas a2200217 4500008004100000245005100041210005100092300001200143490000700155520060500162653002600767653003000793653001600823653001300839653001300852653001100865653001200876653001500888100001600903856008100919 2002 eng d00aInformation technology and literacy assessment0 aInformation technology and literacy assessment a369-3730 v183 aThis column discusses information technology and literacy assessment in the past and present. The author also describes computer-based assessments today including the following topics: computer-scored testing, computer-administered formal assessment, Internet formal assessment, computerized adaptive tests, placement tests, informal assessment, electronic portfolios, information management, and Internet information dissemination. A model of the major present-day applications of information technologies in reading and literacy assessment is also included. (PsycINFO Database Record (c) 2005 APA )10aComputer Applications10aComputer Assisted Testing10aInformation10aInternet10aLiteracy10aModels10aSystems10aTechnology1 aBalajthy, E uhttp://mail.iacat.org/content/information-technology-and-literacy-assessment00525nas a2200121 4500008004100000245005100041210005100092260013700143100001800280700001300298700001500311856007700326 2002 eng d00aInnovative item types for computerized testing0 aInnovative item types for computerized testing aIn W. J. van der Linden and C. A. W. Glas (Eds.), Computerized adaptive testing: Theory and practice. Norwell MA: Kluwer (in press).1 aParshall, C G1 aDavey, T1 aPashley, P uhttp://mail.iacat.org/content/innovative-item-types-computerized-testing00521nas a2200133 4500008004100000245009700041210006900138260001900207100001500226700001100241700001300252700001100265856011100276 2002 eng d00aAn investigation of procedures for estimating error indexes in proficiency estimation in CAT0 ainvestigation of procedures for estimating error indexes in prof aNew Orleans LA1 aShyu, C -Y1 aFan, M1 aThompson1 aHsu, Y uhttp://mail.iacat.org/content/investigation-procedures-estimating-error-indexes-proficiency-estimation-cat01184nas a2200133 4500008004100000245006200041210005900103300001200162490000700174520073400181653003400915100001600949856008500965 2002 eng d00aAn item response model for characterizing test compromise0 aitem response model for characterizing test compromise a163-1790 v273 aThis article presents an item response model for characterizing test-compromise that enables the estimation of item-preview and score-gain distributions observed in on-demand high-stakes testing programs. Model parameters and posterior distributions are estimated by Markov Chain Monte Carlo (MCMC) procedures. Results of a simulation study suggest that when at least some of the items taken by a small sample of test takers are known to be secure (uncompromised), the procedure can provide useful summaries of test-compromise and its impact on test scores. The article includes discussions of operational use of the proposed procedure, possible model violations and extensions, and application to computerized adaptive testing. 10acomputerized adaptive testing1 aSegall, D O uhttp://mail.iacat.org/content/item-response-model-characterizing-test-compromise00555nas a2200133 4500008004100000245012100041210006900162300001200231490000700243100001500250700001900265700001300284856012400297 2002 eng d00aItem selection in computerized adaptive testing: Improving the a-stratified design with the Sympson-Hetter algorithm0 aItem selection in computerized adaptive testing Improving the as a376-3920 v261 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://mail.iacat.org/content/item-selection-computerized-adaptive-testing-improving-stratified-design-sympson-hetter-000579nas a2200145 4500008004100000020001400041245012100055210006900176300001200245490000700257100001500264700001900279700001300298856012200311 2002 eng d a0146-621600aItem selection in computerized adaptive testing: Improving the a-stratified design with the Sympson-Hetter algorithm0 aItem selection in computerized adaptive testing Improving the as a376-3920 v261 aLeung, C K1 aChang, Hua-Hua1 aHau, K T uhttp://mail.iacat.org/content/item-selection-computerized-adaptive-testing-improving-stratified-design-sympson-hetter00427nas a2200121 4500008004100000245006500041210006500106260001500171100001100186700001100197700001100208856008600219 2001 eng d00aImpact of item location effects on ability estimation in CAT0 aImpact of item location effects on ability estimation in CAT aSeattle WA1 aLiu, M1 aZhu, R1 aGuo, F uhttp://mail.iacat.org/content/impact-item-location-effects-ability-estimation-cat00442nas a2200133 4500008004100000245005900041210005900100260001500159100001000174700001600184700001300200700001600213856007900229 2001 eng d00aImpact of scoring options for not reached items in CAT0 aImpact of scoring options for not reached items in CAT aSeattle WA1 aYi, Q1 aWidiatmo, H1 aBan, J-C1 aHarris, D J uhttp://mail.iacat.org/content/impact-scoring-options-not-reached-items-cat00501nas a2200109 4500008004100000245011600041210006900157260001500226100001200241700001800253856012000271 2001 eng d00aImpact of several computer-based testing variables on the psychometric properties of credentialing examinations0 aImpact of several computerbased testing variables on the psychom aSeattle WA1 aXing, D1 aHambleton, RK uhttp://mail.iacat.org/content/impact-several-computer-based-testing-variables-psychometric-properties-credentialing00622nas a2200109 4500008004100000245018300041210006900224260006700293100001200360700001800372856012200390 2001 eng d00aImpact of several computer-based testing variables on the psychometric properties of credentialing examinations (Laboratory of Psychometric and Evaluative Research Report No 393)0 aImpact of several computerbased testing variables on the psychom aAmherst, MA: University of Massachusetts, School of Education.1 aXing, D1 aHambleton, RK uhttp://mail.iacat.org/content/impact-several-computer-based-testing-variables-psychometric-properties-credentialing-000421nas a2200097 4500008004100000245007200041210006900113260003000182100001800212856009300230 2001 eng d00aImplementing constrained CAT with shadow tests for large item pools0 aImplementing constrained CAT with shadow tests for large item po aSubmitted for publication1 aVeldkamp, B P uhttp://mail.iacat.org/content/implementing-constrained-cat-shadow-tests-large-item-pools00590nas a2200109 4500008004100000245012400041210006900165260008200234100001900316700002300335856012200358 2001 eng d00aImplementing content constraints in a-stratified adaptive testing using a shadow test approach (Research Report 01-001)0 aImplementing content constraints in astratified adaptive testing aUniversity of Twente, Department of Educational Measurement and Data Analysis1 aChang, Hua-Hua1 avan der Linden, WJ uhttp://mail.iacat.org/content/implementing-content-constraints-stratified-adaptive-testing-using-shadow-test-approach00475nas a2200109 4500008004100000245008400041210006900125260004000194100001200234700001500246856010400261 2001 eng d00aThe influence of item characteristics and administration position on CAT Scores0 ainfluence of item characteristics and administration position on aHudson Valley, NY, October 26, 20011 aWang, L1 aGawlick, L uhttp://mail.iacat.org/content/influence-item-characteristics-and-administration-position-cat-scores00495nas a2200121 4500008004100000245008700041210006900128260001500197100001600212700001900228700001300247856011300260 2001 eng d00aIntegrating stratification and information approaches for multiple constrained CAT0 aIntegrating stratification and information approaches for multip aSeattle WA1 aLeung, C -I1 aChang, Hua-Hua1 aHau, K-T uhttp://mail.iacat.org/content/integrating-stratification-and-information-approaches-multiple-constrained-cat00575nas a2200133 4500008004100000245014400041210006900185260001500254100001500269700001100284700001300295700000900308856012400317 2001 eng d00aAn investigation of procedures for estimating error indexes in proficiency estimation in a realistic second-order equitable CAT environment0 ainvestigation of procedures for estimating error indexes in prof aSeattle WA1 aShyu, C -Y1 aFan, M1 aThompson1 aHsu. uhttp://mail.iacat.org/content/investigation-procedures-estimating-error-indexes-proficiency-estimation-realistic-second00494nas a2200121 4500008004100000245009500041210006900136260001500205100001800220700001400238700001900252856010100271 2001 eng d00aAn investigation of the impact of items that exhibit mild DIF on ability estimation in CAT0 ainvestigation of the impact of items that exhibit mild DIF on ab aSeattle WA1 aJennings, J A1 aDodd, B G1 aFitzpatrick, S uhttp://mail.iacat.org/content/investigation-impact-items-exhibit-mild-dif-ability-estimation-cat00584nas a2200121 4500008004100000245015600041210006900197260002600266100001500292700001500307700002000322856012000342 2001 eng d00aItem and passage selection algorithm simulations for a computerized adaptive version of the verbal section of the Medical College Admission Test (MCAT)0 aItem and passage selection algorithm simulations for a computeri aMCAT Monograph Series1 aSmith, R W1 aPlake, B S1 ade Ayala, R. J. uhttp://mail.iacat.org/content/item-and-passage-selection-algorithm-simulations-computerized-adaptive-version-verbal00363nas a2200097 4500008004100000245005300041210005300094260002000147100001700167856008100184 2001 eng d00aItem pool design for computerized adaptive tests0 aItem pool design for computerized adaptive tests aAachen, Germany1 aReckase, M D uhttp://mail.iacat.org/content/item-pool-design-computerized-adaptive-tests-001466nas a2200253 4500008004100000245013900041210006900180260005000249300001200299520053700311653002100848653002500869653001200894653002900906653002200935653002700957653002600984653001501010653001601025100001501041700001601056700001701072856012301089 2001 eng d00aItem response theory applied to combinations of multiple-choice and constructed-response items--approximation methods for scale scores0 aItem response theory applied to combinations of multiplechoice a aMahwah, N.J. USAbLawrence Erlbaum Associates a289-3153 a(From the chapter) The authors develop approximate methods that replace the scoring tables with weighted linear combinations of the component scores. Topics discussed include: a linear approximation for the extension to combinations of scores; the generalization of two or more scores; potential applications of linear approximations to item response theory in computerized adaptive tests; and evaluation of the pattern-of-summed-scores, and Gaussian approximation, estimates of proficiency. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aItem Response Theory10aMethod)10aMultiple Choice (Testing10aScoring (Testing)10aStatistical Estimation10aStatistical Weighting10aTest Items10aTest Scores1 aThissen, D1 aNelson, L A1 aSwygert, K A uhttp://mail.iacat.org/content/item-response-theory-applied-combinations-multiple-choice-and-constructed-response-items01986nas a2200205 4500008004100000245010100041210006900142300001200211490000700223520124900230653001201479653002101491653003001512653001501542653001601557653004501573100001701618700001901635856012601654 2001 eng d00aItem selection in computerized adaptive testing: Should more discriminating items be used first?0 aItem selection in computerized adaptive testing Should more disc a249-2660 v383 aDuring computerized adaptive testing (CAT), items are selected continuously according to the test-taker's estimated ability. Test security has become a problem because high-discrimination items are more likely to be selected and become overexposed. So, there seems to be a tradeoff between high efficiency in ability estimations and balanced usage of items. This series of four studies addressed the dilemma by focusing on the notion of whether more or less discriminating items should be used first in CAT. The first study demonstrated that the common maximum information method with J. B. Sympson and R. D. Hetter (1985) control resulted in the use of more discriminating items first. The remaining studies showed that using items in the reverse order, as described in H. Chang and Z. Yings (1999) stratified method had potential advantages: (a) a more balanced item usage and (b) a relatively stable resultant item pool structure with easy and inexpensive management. This stratified method may have ability-estimation efficiency better than or close to that of other methods. It is argued that the judicious selection of items, as in the stratified method, is a more active control of item exposure. (PsycINFO Database Record (c) 2005 APA )10aability10aAdaptive Testing10aComputer Assisted Testing10aEstimation10aStatistical10aTest Items computerized adaptive testing1 aHau, Kit-Tai1 aChang, Hua-Hua uhttp://mail.iacat.org/content/item-selection-computerized-adaptive-testing-should-more-discriminating-items-be-used-first01223nas a2200145 4500008004100000245009700041210006900138300001200207490000600219520069600225100001500921700001400936700001400950856011300964 2000 eng d00aThe impact of receiving the same items on consecutive computer adaptive test administrations0 aimpact of receiving the same items on consecutive computer adapt a131-1510 v13 aAddresses item exposure in a Computerized Adaptive Test (CAT) when the item selection algorithm is permitted to present examinees with questions that they have already been asked in a previous test administration. The data were from a national certification exam in medical technology. The responses of 178 repeat examinees were compared. The results indicate that the combined use of an adaptive algorithm to select items and latent trait theory to estimate person ability provides substantial protection from score contamination. The implications for constraints that prohibit examinees from seeing an item twice are discussed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aO'Neill, T1 aLunz, M E1 aThiede, K uhttp://mail.iacat.org/content/impact-receiving-same-items-consecutive-computer-adaptive-test-administrations00508nas a2200097 4500008004100000245014000041210006900181260002000250100001500270856012500285 2000 eng d00aImplementing the computer-adaptive sequential testing (CAST) framework to mass produce high quality computer-adaptive and mastery tests0 aImplementing the computeradaptive sequential testing CAST framew aNew Orleans, LA1 aLuecht, RM uhttp://mail.iacat.org/content/implementing-computer-adaptive-sequential-testing-cast-framework-mass-produce-high-quality01173nas a2200205 4500008004100000245005600041210005300097300001200150490000700162520055300169653002200722653002500744653002500769653002200794653001500816100002300831700001800854700001500872856008000887 2000 eng d00aAn integer programming approach to item bank design0 ainteger programming approach to item bank design a139-1500 v243 aAn integer programming approach to item bank design is presented that can be used to calculate an optimal blueprint for an item bank, in order to support an existing testing program. The results are optimal in that they minimize the effort involved in producing the items as revealed by current item writing patterns. Also presented is an adaptation of the models, which can be used as a set of monitoring tools in item bank management. The approach is demonstrated empirically for an item bank that was designed for the Law School Admission Test. 10aAptitude Measures10aItem Analysis (Test)10aItem Response Theory10aTest Construction10aTest Items1 avan der Linden, WJ1 aVeldkamp, B P1 aReese, L M uhttp://mail.iacat.org/content/integer-programming-approach-item-bank-design00618nas a2200121 4500008004100000245016600041210006900207260004700276100001800323700001300341700001500354856012700369 2000 eng d00aAn investigation of approaches to computerizing the GRE subject tests (GRE Board Professional Report No 93-08P; Educational Testing Service Research Report 00-4)0 ainvestigation of approaches to computerizing the GRE subject tes aPrinceton NJ: Educational Testing Service.1 aStocking, M L1 aSmith, R1 aSwanson, L uhttp://mail.iacat.org/content/investigation-approaches-computerizing-gre-subject-tests-gre-board-professional-report-no-9300453nas a2200097 4500008004100000245004100041210004100082260014500123100001600268856007100284 2000 eng d00aItem calibration and parameter drift0 aItem calibration and parameter drift aW. J. van der linden and C. A. W. Glas (Eds.). Computerized adaptive testing: Theory and practice (pp.183-199). Norwell MA: Kluwer Academic.1 aGlas, C A W uhttp://mail.iacat.org/content/item-calibration-and-parameter-drift00530nas a2200133 4500008004100000245010200041210006900143300001000212490000700222100001600229700001600245700001700261856011800278 2000 eng d00aItem exposure control in computer-adaptive testing: The use of freezing to augment stratification0 aItem exposure control in computeradaptive testing The use of fre a28-520 v401 aParshall, C1 aHarmes, J C1 aKromrey, J D uhttp://mail.iacat.org/content/item-exposure-control-computer-adaptive-testing-use-freezing-augment-stratification00315nas a2200097 4500008004100000245001500041210001500056260008500071100001600156856004500172 2000 eng d00aItem pools0 aItem pools aWainer, H. (2000). Computerized adaptive testing: a primer. Mahwah, NJ: Erlbaum.1 aFlaugher, R uhttp://mail.iacat.org/content/item-pools01775nas a2200289 4500008004100000245007700041210006900118300001400187490000700201520080000208653002501008653003101033653003701064653003801101653001901139653001001158653002701168653004601195653002001241653002801261653003201289653001801321100001401339700001701353700001501370856010001385 2000 eng d00aItem response theory and health outcomes measurement in the 21st century0 aItem response theory and health outcomes measurement in the 21st aII28-II420 v383 aItem response theory (IRT) has a number of potential advantages over classical test theory in assessing self-reported health outcomes. IRT models yield invariant item and latent trait estimates (within a linear transformation), standard errors conditional on trait level, and trait estimates anchored to item content. IRT also facilitates evaluation of differential item functioning, inclusion of items with different response formats in the same scale, and assessment of person fit and is ideally suited for implementing computer adaptive testing. Finally, IRT methods can be helpful in developing better health outcome measures and in assessing change over time. These issues are reviewed, along with a discussion of some of the methodological and practical challenges in applying IRT methods.10a*Models, Statistical10aActivities of Daily Living10aData Interpretation, Statistical10aHealth Services Research/*methods10aHealth Surveys10aHuman10aMathematical Computing10aOutcome Assessment (Health Care)/*methods10aResearch Design10aSupport, Non-U.S. Gov't10aSupport, U.S. Gov't, P.H.S.10aUnited States1 aHays, R D1 aMorales, L S1 aReise, S P uhttp://mail.iacat.org/content/item-response-theory-and-health-outcomes-measurement-21st-century01344nas a2200157 4500008004100000245006300041210006300104300001000167490000700177520083100184100002101015700001801036700002001054700002201074856009001096 2000 eng d00aItem selection algorithms in computerized adaptive testing0 aItem selection algorithms in computerized adaptive testing a12-140 v123 aStudied the efficacy of 3 different item selection algorithms in computerized adaptive testing. Ss were 395 university students (aged 20-25 yrs) in Spain. Ss were asked to submit answers via computer to 28 items of a personality questionnaire using item selection algorithms based on maximum item information, entropy, or mixed item-entropy algorithms. The results were evaluated according to ability of Ss to use item selection algorithms and number of questions. Initial results indicate that mixed criteria algorithms were more efficient than information or entropy algorithms for up to 15 questionnaire items, but that differences in efficiency decreased with increasing item number. Implications for developing computer adaptive testing methods are discussed. (PsycINFO Database Record (c) 2002 APA, all rights reserved).1 aGarcia, David, A1 aSanta Cruz, C1 aDorronsoro, J R1 aRubio Franco, V J uhttp://mail.iacat.org/content/item-selection-algorithms-computerized-adaptive-testing00486nas a2200121 4500008004100000245006200041210006200103260005900165300001100224100002300235700001700258856008900275 2000 eng d00aItem selection and ability estimation in adaptive testing0 aItem selection and ability estimation in adaptive testing aDordrecht, The NetherlandsbKluwer Academic Publishers a1–251 avan der Linden, WJ1 aPashley, P J uhttp://mail.iacat.org/content/item-selection-and-ability-estimation-adaptive-testing00387nas a2200109 4500008004100000245005600041210005600097260002100153100001100174700001500185856007700200 1999 eng d00aImpact of flawed items on ability estimation in CAT0 aImpact of flawed items on ability estimation in CAT aMontreal, Canada1 aLiu, M1 aSteffen, M uhttp://mail.iacat.org/content/impact-flawed-items-ability-estimation-cat00535nas a2200109 4500008004100000245013000041210006900171260002100240100002000261700001900281856012500300 1999 eng d00aImplications from information functions and standard errors for determining preferred normed scales for CAT and P and P ASVAB0 aImplications from information functions and standard errors for  aMontreal, Canada1 aNicewander, W A1 aThomasson, G L uhttp://mail.iacat.org/content/implications-information-functions-and-standard-errors-determining-preferred-normed-scales01886nas a2200145 4500008004100000020001100041245008200052210006900134260005300203520133100256100001501587700001801602700001601620856010401636 1999 eng d aSeries00aIncorporating content constraints into a multi-stage adaptive testlet design.0 aIncorporating content constraints into a multistage adaptive tes aPrinceton, NJ. USAbLaw School Admission Council3 aMost large-scale testing programs facing computerized adaptive testing (CAT) must face the challenge of maintaining extensive content requirements, but content constraints in computerized adaptive testing (CAT) can compromise the precision and efficiency that could be achieved by a pure maximum information adaptive testing algorithm. This simulation study first evaluated whether realistic content constraints could be met by carefully assembling testlets and appropriately selecting testlets for each test taker that, when combined, would meet the content requirements of the test and would be adapted to the test takers ability level. The second focus of the study was to compare the precision of the content-balanced testlet design with that achieved by the current paper-and-pencil version of the test through data simulation. The results reveal that constraints to control for item exposure, testlet overlap, and efficient pool utilization need to be incorporated into the testlet assembly algorithm. More refinement of the statistical constraints for testlet assembly is also necessary. However, even for this preliminary attempt at assembling content-balanced testlets, the two-stage computerized test simulated with these testlets performed quite well. (Contains 5 figures, 5 tables, and 12 references.) (Author/SLD)1 aReese, L M1 aSchnipke, D L1 aLuebke, S W uhttp://mail.iacat.org/content/incorporating-content-constraints-multi-stage-adaptive-testlet-design02472nam a2200133 4500008004100000245004300041210004300084260005200127520201600179653003402195100001502229700002402244856007002268 1999 eng d00aInnovations in computerized assessment0 aInnovations in computerized assessment aMahwah, N.J.bLawrence Erlbaum Associates, Inc.3 aChapters in this book present the challenges and dilemmas faced by researchers as they created new computerized assessments, focusing on issues addressed in developing, scoring, and administering the assessments. Chapters are: (1) "Beyond Bells and Whistles; An Introduction to Computerized Assessment" (Julie B. Olson-Buchanan and Fritz Drasgow); (2) "The Development of a Computerized Selection System for Computer Programmers in a Financial Services Company" (Michael J. Zickar, Randall C. Overton, L. Rogers Taylor, and Harvey J. Harms); (3) "Development of the Computerized Adaptive Testing Version of the Armed Services Vocational Aptitude Battery" (Daniel O. Segall and Kathleen E. Moreno); (4) "CAT for Certification and Licensure" (Betty A. Bergstrom and Mary E. Lunz); (5) "Developing Computerized Adaptive Tests for School Children" (G. Gage Kingsbury and Ronald L. Houser); (6) "Development and Introduction of a Computer Adaptive Graduate Record Examinations General Test" (Craig N. Mills); (7) "Computer Assessment Using Visual Stimuli: A Test of Dermatological Skin Disorders" (Terry A. Ackerman, John Evans, Kwang-Seon Park, Claudia Tamassia, and Ronna Turner); (8) "Creating Computerized Adaptive Tests of Music Aptitude: Problems, Solutions, and Future Directions" (Walter P. Vispoel); (9) "Development of an Interactive Video Assessment: Trials and Tribulations" (Fritz Drasgow, Julie B. Olson-Buchanan, and Philip J. Moberg); (10) "Computerized Assessment of Skill for a Highly Technical Job" (Mary Ann Hanson, Walter C. Borman, Henry J. Mogilka, Carol Manning, and Jerry W. Hedge); (11) "Easing the Implementation of Behavioral Testing through Computerization" (Wayne A. Burroughs, Janet Murray, S. Scott Wesley, Debra R. Medina, Stacy L. Penn, Steven R. Gordon, and Michael Catello); and (12) "Blood, Sweat, and Tears: Some Final Comments on Computerized Assessment." (Fritz Drasgow and Julie B. Olson-Buchanan). Each chapter contains references. (Contains 17 tables and 21 figures.) (SLD)10acomputerized adaptive testing1 aDrasgow, F1 aOlson-Buchanan, J B uhttp://mail.iacat.org/content/innovations-computerized-assessment00461nas a2200109 4500008004100000245004100041210004100082260011900123100001600242700002000258856007300278 1999 eng d00aItem calibration and parameter drift0 aItem calibration and parameter drift aW. J. van der Linden and C. A. W. Glas (Eds.), Computer adaptive testing: Theory and practice. Norwell MA: Kluwer.1 aGlas, C A W1 aVeerkamp, W J J uhttp://mail.iacat.org/content/item-calibration-and-parameter-drift-000486nas a2200121 4500008004100000245008600041210006900127260001600196100001600212700001500228700001500243856010600258 1999 eng d00aItem exposure in adaptive tests: An empirical investigation of control strategies0 aItem exposure in adaptive tests An empirical investigation of co aLawrence KS1 aParshall, C1 aHogarty, K1 aKromrey, J uhttp://mail.iacat.org/content/item-exposure-adaptive-tests-empirical-investigation-control-strategies00474nas a2200097 4500008004100000245008900041210006900130260004700199100001900246856011100265 1999 eng d00aItem nonresponse: Occurrence, causes and imputation of missing answers to test items0 aItem nonresponse Occurrence causes and imputation of missing ans a(M and T Series No 32). Leiden: DSWO Press1 aHuisman, J M E uhttp://mail.iacat.org/content/item-nonresponse-occurrence-causes-and-imputation-missing-answers-test-items00437nas a2200109 4500008004100000245008200041210006900123300001200192490000700204100001600211856010000227 1999 eng d00aItem selection in adaptive testing with the sequential probability ratio test0 aItem selection in adaptive testing with the sequential probabili a249-2610 v231 aEggen, Theo uhttp://mail.iacat.org/content/item-selection-adaptive-testing-sequential-probability-ratio-test00541nas a2200121 4500008004100000245012100041210006900162260001700231100001500248700001900263700001300282856012400295 1999 eng d00aItem selection in computerized adaptive testing: improving the a-stratified design with the Sympson-Hetter algorithm0 aItem selection in computerized adaptive testing improving the as aMontreal, CA1 aLeung, C-K1 aChang, Hua-Hua1 aHau, K-T uhttp://mail.iacat.org/content/item-selection-computerized-adaptive-testing-improving-stratified-design-sympson-hetter-100428nas a2200109 4500008004100000245007600041210006900117260001700186100000700203700001400210856009400224 1998 eng d00aThe impact of nonmodel-fitting responses in a realistic CAT environment0 aimpact of nonmodelfitting responses in a realistic CAT environme aSan Diego CA1 aYi1 aNering, M uhttp://mail.iacat.org/content/impact-nonmodel-fitting-responses-realistic-cat-environment00409nas a2200109 4500008004100000245006800041210006400109260001500173100001100188700001500199856008500214 1998 eng d00aThe impact of scoring flawed items on ability estimation in CAT0 aimpact of scoring flawed items on ability estimation in CAT aUrbana, IL1 aLiu, M1 aSteffen, M uhttp://mail.iacat.org/content/impact-scoring-flawed-items-ability-estimation-cat00554nas a2200097 4500008004100000245008000041210006900121260014400190100001700334856010500351 1998 eng d00aInnovations in computer-based ability testing: Promise, problems and perils0 aInnovations in computerbased ability testing Promise problems an aIn Hakel, M.D. (Ed.) Beyond multiple choice: Alternatives to traditional testing for selection. Hillsdale, NJ: Lawrence Erlbaum Associates.1 aMcBride, J R uhttp://mail.iacat.org/content/innovations-computer-based-ability-testing-promise-problems-and-perils00581nas a2200109 4500008004100000245001700041210001700058490000600075520032700081100001600408856004700424 1998 eng d00aItem banking0 aItem banking0 v63 aDiscusses the advantages and disadvantages of using item banks while providing useful information to those who are considering implementing an item banking project in their school district. The primary advantage of item banking is in test development. Also describes start-up activities in implementing item banking. (SLD)1 aRudner, L M uhttp://mail.iacat.org/content/item-banking00420nas a2200097 4500008004100000245007600041210006900117260001700186100001800203856010100221 1998 eng d00aItem development and pretesting in a computer-based testing environment0 aItem development and pretesting in a computerbased testing envir aPhiladelphia1 aParshall, C G uhttp://mail.iacat.org/content/item-development-and-pretesting-computer-based-testing-environment00517nas a2200097 4500008004100000245013300041210006900174260003500243100001600278856012500294 1998 eng d00aItem selection in adaptive testing with the sequential probability ratio test (Measurement and Research Department Report, 98-1)0 aItem selection in adaptive testing with the sequential probabili aArnhem, The Netherlands: Cito.1 aEggen, Theo uhttp://mail.iacat.org/content/item-selection-adaptive-testing-sequential-probability-ratio-test-measurement-and-research00511nas a2200121 4500008004100000245010100041210006900142300001200211490000700223100001300230700001900243856012700262 1998 eng d00aItem selection in computerized adaptive testing: Should more discriminating items be used first?0 aItem selection in computerized adaptive testing Should more disc a249-2660 v381 aHau, K T1 aChang, Hua-Hua uhttp://mail.iacat.org/content/item-selection-computerized-adaptive-testing-should-more-discriminating-items-be-used-firs-000570nas a2200097 4500008004100000245020300041210006900244100001300313700001900326856012700345 1998 eng d00aItem selection in computerized adaptive testing: Should more discriminating items be used first? Paper presented at the annual meeting of the American Educational Research Association, San Diego, CA0 aItem selection in computerized adaptive testing Should more disc1 aHau, K T1 aChang, Hua-Hua uhttp://mail.iacat.org/content/item-selection-computerized-adaptive-testing-should-more-discriminating-items-be-used-firs-100471nas a2200121 4500008004100000245006900041210006900110260002500179100001700204700001800221700001400239856009600253 1997 eng d00aIdentifying similar item content clusters on multiple test forms0 aIdentifying similar item content clusters on multiple test forms aGatlinburg, TN, June1 aReckase, M D1 aThompson, T D1 aNering, M uhttp://mail.iacat.org/content/identifying-similar-item-content-clusters-multiple-test-forms00464nas a2200097 4500008004100000245009100041210006900132260003700201100001700238856011100255 1997 eng d00aImproving the quality of music aptitude tests through adaptive administration of items0 aImproving the quality of music aptitude tests through adaptive a aUniversity of Iowa, Iowa City IA1 aVispoel, W P uhttp://mail.iacat.org/content/improving-quality-music-aptitude-tests-through-adaptive-administration-items00537nas a2200121 4500008004100000245009400041210006900135260004600204100001500250700001800265700001600283856011600299 1997 eng d00aIncorporating content constraints into a multi-stage adaptive testlet design: LSAC report0 aIncorporating content constraints into a multistage adaptive tes aNewtown, PA: Law School Admission Council1 aReese, L M1 aSchnipke, D L1 aLuebke, S W uhttp://mail.iacat.org/content/incorporating-content-constraints-multi-stage-adaptive-testlet-design-lsac-report00427nas a2200109 4500008004100000245007200041210006900113260001200182100001300194700001300207856009700220 1997 eng d00aIncorporating decision consistency into Bayesian sequential testing0 aIncorporating decision consistency into Bayesian sequential test aChicago1 aSmith, R1 aLewis, C uhttp://mail.iacat.org/content/incorporating-decision-consistency-bayesian-sequential-testing00513nas a2200145 4500008004100000245008100041210006900122300001200191490000700203100001500210700001400225700001200239700001600251856010000267 1997 eng d00aAn investigation of self-adapted testing in a Spanish high school population0 ainvestigation of selfadapted testing in a Spanish high school po a210-2210 v571 aPonsoda, V1 aWise, S L1 aOlea, J1 aRevuelta, J uhttp://mail.iacat.org/content/investigation-self-adapted-testing-spanish-high-school-population00923nas a2200145 4500008004100000245003900041210003800080260006100118300001200179520047000191100001600661700001700677700001700694856006600711 1997 eng d00aItem exposure control in CAT-ASVAB0 aItem exposure control in CATASVAB aWashington D.C., USAbAmerican Psychological Association a141-1443 aDescribes the method used to control item exposure in computerized adaptive testing-Armed Services Vocational Aptitude Battery (CAT-ASVAB). The method described was developed specifically to ensure that CAT-ASVAB items were expose no more often than the items in the printers ASVAB's alternate forms, ensuring that CAT ASVAB is nor more vulnerable than printed ASVAB forms to comprise from item exposure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)1 aHetter, R D1 aSympson, J B1 aMcBride, J R uhttp://mail.iacat.org/content/item-exposure-control-cat-asvab00544nas a2200121 4500008004100000245004100041210004100082260018000123100001600303700001600319700001600335856007100351 1997 eng d00aItem pool development and evaluation0 aItem pool development and evaluation aW. A. Sands, B. K. Waters, and J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 117-130). Washington DC: American Psychological Association.1 aSegall, D O1 aMoreno, K E1 aHetter, D H uhttp://mail.iacat.org/content/item-pool-development-and-evaluation00329nas a2200097 4500008004100000245004200041210004200083260001500125100001900140856007200159 1997 eng d00aItem pool development and maintenance0 aItem pool development and maintenance aChicago IL1 aKingsbury, G G uhttp://mail.iacat.org/content/item-pool-development-and-maintenance00312nas a2200097 4500008004100000245003700041210003700078260001300115100001900128856006700147 1996 eng d00aItem review and adaptive testing0 aItem review and adaptive testing aNew York1 aKingsbury, G G uhttp://mail.iacat.org/content/item-review-and-adaptive-testing00637nas a2200097 4500008004100000245010900041210006900150260018000219100001400399856012600413 1995 eng d00aImproving individual differences measurement with item response theory and computerized adaptive testing0 aImproving individual differences measurement with item response  aD. Lubinski and R. V. Dawis (Eds.), Assessing individual differences in human behavior: New concepts, methods, and findings (pp. 49-79). Palo Alto CA: Davies-Black Publishing.1 aWeiss, DJ uhttp://mail.iacat.org/content/improving-individual-differences-measurement-item-response-theory-and-computerized-adaptive00450nas a2200097 4500008004100000245004400041210004400085260013900129100001700268856006700285 1995 eng d00aIndividualized testing in the classroom0 aIndividualized testing in the classroom aAnderson, L.W. (Ed.), International Encyclopedia of Teaching and Teacher Education. Oxford, New York, Tokyo: Elsevier Science 295-299.1 aLinacre, J M uhttp://mail.iacat.org/content/individualized-testing-classroom00478nas a2200109 4500008004100000245009500041210006900136260002100205100001100226700001600237856011500253 1995 eng d00aThe influence of examinee test-taking behavior motivation in computerized adaptive testing0 ainfluence of examinee testtaking behavior motivation in computer aSan Francisco CA1 aKim, J1 aMcLean, J E uhttp://mail.iacat.org/content/influence-examinee-test-taking-behavior-motivation-computerized-adaptive-testing00649nas a2200133 4500008004100000245017200041210006900213260004600282100001900328700001700347700001500364700001300379856012300392 1995 eng d00aThe introduction and comparability of the computer-adaptive GRE General Test (GRE Board Professional Report 88-08ap; Educational Testing Service Research Report 95-20)0 aintroduction and comparability of the computeradaptive GRE Gener aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M L1 aMills, C N1 aDurso, R uhttp://mail.iacat.org/content/introduction-and-comparability-computer-adaptive-gre-general-test-gre-board-professional00475nas a2200109 4500008004100000245009300041210006900134260002200203100001600225700001300241856011100254 1995 eng d00aAn investigation of item calibration procedures for a computerized licensure examination0 ainvestigation of item calibration procedures for a computerized  aSan Francisco, CA1 aHaynie, K A1 aWay, W D uhttp://mail.iacat.org/content/investigation-item-calibration-procedures-computerized-licensure-examination00514nas a2200121 4500008004100000245011200041210006900153300001300222490000700235100001400242700001400256856012200270 1995 eng d00aAn investigation of procedures for computerized adaptive testing using the successive intervals Rasch model0 ainvestigation of procedures for computerized adaptive testing us a976-990.0 v551 aKoch, W R1 aDodd, B G uhttp://mail.iacat.org/content/investigation-procedures-computerized-adaptive-testing-using-successive-intervals-rasch00447nam a2200097 4500008004100000245007200041210006900113260006100182100001200243856009400255 1995 eng d00aItem equivalence from paper-and-pencil to computer adaptive testing0 aItem equivalence from paperandpencil to computer adaptive testin aUnpublished doctoral dissertation, University of Chicago1 aChae, S uhttp://mail.iacat.org/content/item-equivalence-paper-and-pencil-computer-adaptive-testing00507nas a2200121 4500008004100000245009100041210006900132260002100201100001600222700001300238700001700251856011700268 1995 eng d00aItem exposure rates for unconstrained and content-balanced computerized adaptive tests0 aItem exposure rates for unconstrained and contentbalanced comput aSan Francisco CA1 aMorrison, C1 aSubhiyah1 aNungester, R uhttp://mail.iacat.org/content/item-exposure-rates-unconstrained-and-content-balanced-computerized-adaptive-tests00400nas a2200097 4500008004100000245006700041210006700108260001900175100001400194856009400208 1995 eng d00aItem review and answer changing in computerized adaptive tests0 aItem review and answer changing in computerized adaptive tests aTrier, Germany1 aWise, S L uhttp://mail.iacat.org/content/item-review-and-answer-changing-computerized-adaptive-tests00432nas a2200109 4500008004100000245007100041210006900112300001200181490001800193100001600211856009500227 1995 eng d00aItem times in computerized testing: A new differential information0 aItem times in computerized testing A new differential informatio a108-1090 v11 (Suppl. 1)1 aHornke, L F uhttp://mail.iacat.org/content/item-times-computerized-testing-new-differential-information00525nas a2200121 4500008004100000245011800041210006900159300001200228490000700240100001800247700001600265856012200281 1994 eng d00aThe incomplete equivalence of the paper-and-pencil and computerized versions of the General Aptitude Test Battery0 aincomplete equivalence of the paperandpencil and computerized ve a852-8590 v791 aVan de Vijver1 aHarsveld, M uhttp://mail.iacat.org/content/incomplete-equivalence-paper-and-pencil-and-computerized-versions-general-aptitude-test00572nas a2200133 4500008004100000245013900041210006900180300001000249490000600259100001700265700001700282700001200299856012700311 1994 eng d00aIndividual differences and test administration procedures: A comparison of fixed-item, computerized adaptive, and self-adapted testing0 aIndividual differences and test administration procedures A comp a53-790 v71 aVispoel, W P1 aRocklin, T R1 aWang, T uhttp://mail.iacat.org/content/individual-differences-and-test-administration-procedures-comparison-fixed-item-computerized00509nas a2200109 4500008004100000245012100041210006900162260001900231100001500250700001400265856012000279 1994 eng d00aItem calibration considerations: A comparison of item calibrations on written and computerized adaptive examinations0 aItem calibration considerations A comparison of item calibration aNew Orleans LA1 aStone, G E1 aLunz, M E uhttp://mail.iacat.org/content/item-calibration-considerations-comparison-item-calibrations-written-and-computerized00522nas a2200109 4500008004100000245012600041210006900167260001500236100001700251700001700268856012700285 1993 eng d00aIndividual differences and test administration procedures: A comparison of fixed-item, adaptive, and self-adapted testing0 aIndividual differences and test administration procedures A comp aAtlanta GA1 aVispoel, W P1 aRocklin, T R uhttp://mail.iacat.org/content/individual-differences-and-test-administration-procedures-comparison-fixed-item-adaptive-and00376nas a2200097 4500008004100000245006000041210006000101260001900161100001100180856008700191 1993 eng d00aIndividual differences in computerized adaptive testing0 aIndividual differences in computerized adaptive testing aNew Orleans LA1 aKim, J uhttp://mail.iacat.org/content/individual-differences-computerized-adaptive-testing00518nas a2200121 4500008004100000245008100041210006900122260004600191100001900237700001500256700002100271856010400292 1993 eng d00aIntroduction of a computer adaptive GRE General test (Research Report 93-57)0 aIntroduction of a computer adaptive GRE General test Research Re aPrinceton NJ: Educational Testing Service1 aSchaeffer, G A1 aSteffen, M1 aGolub-Smith, M L uhttp://mail.iacat.org/content/introduction-computer-adaptive-gre-general-test-research-report-93-5700415nas a2200121 4500008004100000245005600041210005200097260001500149100001400164700001900178700001600197856008000213 1993 eng d00aAn investigation of restricted self-adapted testing0 ainvestigation of restricted selfadapted testing aAtlanta GA1 aWise, S L1 aKingsbury, G G1 aHouser, R L uhttp://mail.iacat.org/content/investigation-restricted-self-adapted-testing00544nas a2200121 4500008004100000245009600041210006900137260005100206100001600257700001600273700001600289856011700305 1993 eng d00aItem Calibration: Medium-of-administration effect on computerized adaptive scores (TR-93-9)0 aItem Calibration Mediumofadministration effect on computerized a aNavy Personnel Research and Development Center1 aHetter, R D1 aBloxom, B M1 aSegall, D O uhttp://mail.iacat.org/content/item-calibration-medium-administration-effect-computerized-adaptive-scores-tr-93-900430nas a2200109 4500008004100000245007900041210006900120300001000189490000700199100001700206856009700223 1992 eng d00aImproving the measurement of tonal memory with computerized adaptive tests0 aImproving the measurement of tonal memory with computerized adap a73-890 v111 aVispoel, W P uhttp://mail.iacat.org/content/improving-measurement-tonal-memory-computerized-adaptive-tests00434nas a2200109 4500008004100000245007200041210006900113260001800182100001200200700001700212856009500229 1992 eng d00aIncorporating post-administration item response revision into a CAT0 aIncorporating postadministration item response revision into a C aSan Francisco1 aWang, M1 aWingersky, M uhttp://mail.iacat.org/content/incorporating-post-administration-item-response-revision-cat00392nas a2200109 4500008004100000245006200041210005800103300001200161490000700173100002000180856008200200 1992 eng d00aThe influence of dimensionality on CAT ability estimation0 ainfluence of dimensionality on CAT ability estimation a513-5280 v521 ade Ayala, R. J. uhttp://mail.iacat.org/content/influence-dimensionality-cat-ability-estimation00482nas a2200121 4500008004100000245008900041210006900130300001000199490000700209100001500216700001600231856011300247 1992 eng d00aItem selection using an average growth approximation of target information functions0 aItem selection using an average growth approximation of target i a41-510 v161 aLuecht, RM1 aHirsch, T M uhttp://mail.iacat.org/content/item-selection-using-average-growth-approximation-target-information-functions00469nas a2200097 4500008004100000245010200041210006900143100001600212700001700228856012600245 1991 eng d00aIndividual differences in computer adaptive testing: Anxiety, computer literacy, and satisfaction0 aIndividual differences in computer adaptive testing Anxiety comp1 aGershon, RC1 aBergstrom, B uhttp://mail.iacat.org/content/individual-differences-computer-adaptive-testing-anxiety-computer-literacy-and-satisfaction00440nas a2200121 4500008004100000245006100041210006000102300001200162490000700174653003400181100001500215856008800230 1991 eng d00aInter-subtest branching in computerized adaptive testing0 aIntersubtest branching in computerized adaptive testing a140-1410 v5210acomputerized adaptive testing1 aChang, S-H uhttp://mail.iacat.org/content/inter-subtest-branching-computerized-adaptive-testing00444nas a2200121 4500008004100000245006600041210006500107260001400172100001500186700002000201700001700221856008400238 1990 eng d00aIllustration of computerized adaptive testing with the MMPI-20 aIllustration of computerized adaptive testing with the MMPI2 aBoston MA1 aRoper, B L1 aBen-Porath, Y S1 aButcher, J N uhttp://mail.iacat.org/content/illustration-computerized-adaptive-testing-mmpi-200347nas a2200097 4500008004100000245002800041210002800069260008600097100001100183856005500194 1990 eng d00aImportant issues in CAT0 aImportant issues in CAT aH. Wainer et al., Computerized adaptive testing: A primer. Hillsdale NJ: Erlbaum.1 aWainer uhttp://mail.iacat.org/content/important-issues-cat00368nas a2200097 4500008004100000245002900041210002900070260010100099100001100200856005900211 1990 eng d00aIntroduction and history0 aIntroduction and history aIn H. Wainer (Ed.), Computerized adaptive testing: A Primer (pp. 1 - 21). Hillsdale NJ: Erlbaum.1 aWainer uhttp://mail.iacat.org/content/introduction-and-history00516nas a2200109 4500008004100000245007100041210006900112260009800181100001100279700001700290856009900307 1990 eng d00aItem response theory, item calibration, and proficiency estimation0 aItem response theory item calibration and proficiency estimation aH. Wainer (Ed.), Computerized adaptive testing: A primer (pp. 65-102). Hillsdale NJ: Erlbaum.1 aWainer1 aMislevy, R J uhttp://mail.iacat.org/content/item-response-theory-item-calibration-and-proficiency-estimation00408nas a2200097 4500008004100000245007000041210006900111260002100180100001500201856009400216 1989 eng d00aIndividual differences in item selection in self adaptive testing0 aIndividual differences in item selection in self adaptive testin aSan Francisco CA1 aRocklin, T uhttp://mail.iacat.org/content/individual-differences-item-selection-self-adaptive-testing00594nas a2200097 4500008004100000245018700041210006900228260005500297100001700352856012700369 1989 eng d00aThe interpretation and application of multidimensional item response theory models; and computerized testing in the instructional environment: Final Report (Research Report ONR 89-2)0 ainterpretation and application of multidimensional item response aIowa City IA: The American College Testing Program1 aReckase, M D uhttp://mail.iacat.org/content/interpretation-and-application-multidimensional-item-response-theory-models-and-computerized00472nas a2200109 4500008004100000245009300041210006900134260002100203100001400224700001400238856011000252 1989 eng d00aInvestigating the validity of a computerized adaptive test for different examinee groups0 aInvestigating the validity of a computerized adaptive test for d aSan Francisco CA1 aBuhr, D C1 aLegg, S M uhttp://mail.iacat.org/content/investigating-validity-computerized-adaptive-test-different-examinee-groups00494nas a2200121 4500008004100000245009800041210006900139300001200208490000600220100001400226700001400240856011800254 1989 eng d00aAn investigation of procedures for computerized adaptive testing using partial credit scoring0 ainvestigation of procedures for computerized adaptive testing us a335-3570 v21 aKoch, W R1 aDodd, B G uhttp://mail.iacat.org/content/investigation-procedures-computerized-adaptive-testing-using-partial-credit-scoring00590nas a2200109 4500008004100000245012200041210006900163260009400232100001600326700001400342856012400356 1989 eng d00aItem-presentation controls for computerized adaptive testing: Content-balancing versus min-CAT (Research Report 89-1)0 aItempresentation controls for computerized adaptive testing Cont aBaltimore MD: Johns Hopkins University, Department of Psychology, Psychometric Laboratory1 aThomas, T J1 aGreen, BF uhttp://mail.iacat.org/content/item-presentation-controls-computerized-adaptive-testing-content-balancing-versus-min-cat00497nas a2200109 4500008004100000245012500041210006900166300001000235490000600245100001200251856012400263 1988 eng d00aIntroduction to item response theory and computerized adaptive testing as applied in licensure and certification testing0 aIntroduction to item response theory and computerized adaptive t a11-170 v61 aZara, A uhttp://mail.iacat.org/content/introduction-item-response-theory-and-computerized-adaptive-testing-applied-licensure-and00457nas a2200133 4500008004100000245006600041210006600107300001200173490000700185100000900192700001400201700002200215856008600237 1988 eng d00aItem pool maintenance in the presence of item parameter drift0 aItem pool maintenance in the presence of item parameter drift a275-2850 v251 aBock1 aMuraki, E1 aPfeiffenberger, W uhttp://mail.iacat.org/content/item-pool-maintenance-presence-item-parameter-drift00508nas a2200097 4500008004100000245007400041210006900115260011200184100001700296856009700313 1987 eng d00aImproving the measurement of musical ability through adaptive testing0 aImproving the measurement of musical ability through adaptive te aG. Hayes (Ed.), Proceedings of the 29th International ADCIS Conference (pp. 221-228). Bellingham WA: ADCIS.1 aVispoel, W P uhttp://mail.iacat.org/content/improving-measurement-musical-ability-through-adaptive-testing00444nas a2200121 4500008003900000245007300039210006900112300001200181490000700193100001100200700001500211856009600226 1987 d00aItem clusters and computerized adaptive testing: A case for testlets0 aItem clusters and computerized adaptive testing A case for testl a185-2010 v241 aWainer1 aKiely, G L uhttp://mail.iacat.org/content/item-clusters-and-computerized-adaptive-testing-case-testlets00522nas a2200121 4500008004100000245011900041210006900160300001200229490000700241100001500248700001600263856012100279 1985 eng d00aImplications for altering the context in which test items appear: A historical perspective on an immediate concern0 aImplications for altering the context in which test items appear a387-4130 v551 aLeary, L F1 aDorans, N J uhttp://mail.iacat.org/content/implications-altering-context-which-test-items-appear-historical-perspective-immediate00381nas a2200097 4500008004100000245001700041210001700058260014700075100001400222856004700236 1985 eng d00aIntroduction0 aIntroduction aIn D. J. Weiss (Ed.), New horizons in testing: Latent trait test theory and computerized adaptive testing (pp. 1-8). New York: Academic Press.1 aWeiss, DJ uhttp://mail.iacat.org/content/introduction00319nas a2200121 4500008004100000245002700041210002700068300001200095490000600107100001500113700001500128856005400143 1984 eng d00aIssues in item banking0 aIssues in item banking a315-3300 v11 aMillman, J1 aArter, J A uhttp://mail.iacat.org/content/issues-item-banking00488nas a2200121 4500008004500000245008700045210006900132300001200201490000600213100001800219700001600237856011300253 1984 Engldsh 00aItem Location Effects and Their Implications for IRT Equating and Adaptive Testing0 aItem Location Effects and Their Implications for IRT Equating an a147-1540 v81 aKingston, N M1 aDorans, N J uhttp://mail.iacat.org/content/item-location-effects-and-their-implications-irt-equating-and-adaptive-testing00548nas a2200109 4500008004100000245010400041210006900145260006600214100001600280700001700296856012500313 1983 eng d00aInfluence of fallible item parameters on test information during adaptive testing (Tech Rep 83-15).0 aInfluence of fallible item parameters on test information during aSan Diego CA: Navy Personnel Research and Development Center.1 aWetzel, C D1 aMcBride, J R uhttp://mail.iacat.org/content/influence-fallible-item-parameters-test-information-during-adaptive-testing-tech-rep-83-1500478nas a2200109 4500008004100000245010600041210006900147300000900216490000700225100001100232856012500243 1983 eng d00aOn item response theory and computerized adaptive testing: The coming technical revolution in testing0 aitem response theory and computerized adaptive testing The comin a9-160 v281 aWainer uhttp://mail.iacat.org/content/item-response-theory-and-computerized-adaptive-testing-coming-technical-revolution-testing00423nas a2200109 4500008004500000245007100045210006900116300001200185490000600197100001400203856009600217 1982 Engldsh 00aImproving Measurement Quality and Efficiency with Adaptive Testing0 aImproving Measurement Quality and Efficiency with Adaptive Testi a473-4920 v61 aWeiss, DJ uhttp://mail.iacat.org/content/improving-measurement-quality-and-efficiency-adaptive-testing00680nas a2200109 4500008004100000245010300041210006900144260020000213100001700413700001300430856012700443 1982 eng d00aItem Calibrations for Computerized Adaptive Testing (CAT) Experimental Item Pools Adaptive Testing0 aItem Calibrations for Computerized Adaptive Testing CAT Experime aD. J. Weiss (Ed.). Proceedings of the 1982 Computerized Adaptive Testing Conference (pp. 290-294). Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aSympson, J B1 aHartmann uhttp://mail.iacat.org/content/item-calibrations-computerized-adaptive-testing-cat-experimental-item-pools-adaptive-testing00472nas a2200133 4500008004100000245007200041210006900113300001200182490000600194100001400200700001700214700001500231856009200246 1980 eng d00aImplied orders tailored testing: Simulation with the Stanford-Binet0 aImplied orders tailored testing Simulation with the StanfordBine a157-1630 v41 aCudeck, R1 aMcCormick, D1 aCliff, N A uhttp://mail.iacat.org/content/implied-orders-tailored-testing-simulation-stanford-binet00478nas a2200133 4500008004500000245007200045210006900117300001200186490000600198100001400204700001900218700001300237856009400250 1980 Engldsh 00aImplied Orders Tailored Testing: Simulation with the Stanford-Binet0 aImplied Orders Tailored Testing Simulation with the StanfordBine a157-1630 v41 aCudeck, R1 aMcCormick, D J1 aCliff, N uhttp://mail.iacat.org/content/implied-orders-tailored-testing-simulation-stanford-binet-000507nas a2200109 4500008004100000245005900041210005900100260013300159100001700292700001300309856007500322 1980 eng d00aIndividualized testing on the basis of the Rasch model0 aIndividualized testing on the basis of the Rasch model aIn J. Th. Van der Kamp, W. F. Langerak, and D. N. M. de Gruijter (Eds.). Psychometrics for educational debates. New York: Wiley.1 aFischer, G H1 aPendl, P uhttp://mail.iacat.org/content/individualized-testing-basis-rasch-model00529nas a2200121 4500008004100000245007600041210006900117260008100186100001500267700001400282700001700296856009400313 1978 eng d00aImplied orders as a basis for tailored testing (Technical Report No. 6)0 aImplied orders as a basis for tailored testing Technical Report  aLos Angeles CA: University of Southern California, Department of Psychology.1 aCliff, N A1 aCudeck, R1 aMcCormick, D uhttp://mail.iacat.org/content/implied-orders-basis-tailored-testing-technical-report-no-600636nas a2200097 4500008003900000245010600039210006900145260018600214100001300400856012500413 1977 d00aImplementation of a Model Adaptive Testing System at an Armed Forces Entrance and Examination Station0 aImplementation of a Model Adaptive Testing System at an Armed Fo aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program.1 aRee, M J uhttp://mail.iacat.org/content/implementation-model-adaptive-testing-system-armed-forces-entrance-and-examination-station00571nas a2200097 4500008003900000245007100039210006900110260018500179100001800364856009100382 1977 d00aImplementation of Tailored Testing at the Civil Service Commission0 aImplementation of Tailored Testing at the Civil Service Commissi aD. J. Weiss (Ed.), Proceedings of the 1977 Computerized Adaptive Testing Conference. Minneapolis MN: University of Minnesota, Department of Psychology, Psychometric Methods Program1 aMcKillip, R H uhttp://mail.iacat.org/content/implementation-tailored-testing-civil-service-commission00606nas a2200121 4500008004100000245013200041210006900173260007200242100001500314700001400329700001800343856012300361 1977 eng d00aAn information comparison of conventional and adaptive tests in the measurement of classroom achievement (Research Report 77-7)0 ainformation comparison of conventional and adaptive tests in the aMinneapolis: Department of Psychology, Psychometric Methods Program1 aBejar, I I1 aWeiss, DJ1 aGialluca, K A uhttp://mail.iacat.org/content/information-comparison-conventional-and-adaptive-tests-measurement-classroom-achievement00481nam a2200097 4500008004100000245004700041210004700088260015600135100001500291856007700306 1976 eng d00aIncomplete orders and computerized testing0 aIncomplete orders and computerized testing aIn C. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 18-23). Washington DC: U.S. Government Printing Office.1 aCliff, N A uhttp://mail.iacat.org/content/incomplete-orders-and-computerized-testing00516nas a2200109 4500008004100000245005200041210005200093260015600145100001700301700001400318856007400332 1976 eng d00aItem parameterization procedures for the future0 aItem parameterization procedures for the future aC. K. Clark (Ed.), Proceedings of the First Conference on Computerized Adaptive Testing (pp. 107-112.). Washington DC: U.S. Government Printing Office.1 aSchmidt, F L1 aUrry, V W uhttp://mail.iacat.org/content/item-parameterization-procedures-future00530nas a2200097 4500008004100000245006400041210006400105260015600169100001300325856009400338 1974 eng d00aIndividualized testing and item characteristic curve theory0 aIndividualized testing and item characteristic curve theory aD. H. Krantz, R. C. Atkinson, R. D. Luce, and P. Suppes (Eds.), Contemporary developments in mathematical psychology (Vol. II). San Francisco: Freeman.1 aLord, FM uhttp://mail.iacat.org/content/individualized-testing-and-item-characteristic-curve-theory00469nas a2200109 4500008004100000245009900041210006900140300001200209490000600221100001700227856011500244 1974 eng d00aAn interactive computer program for tailored testing based on the one-parameter logistic model0 ainteractive computer program for tailored testing based on the o a208-2120 v61 aReckase, M D uhttp://mail.iacat.org/content/interactive-computer-program-tailored-testing-based-one-parameter-logistic-model00570nas a2200109 4500008004100000245013800041210006900179260005100248100001800299700001600317856012700333 1973 eng d00aImplementation of a Bayesian system for decision analysis in a program of individually prescribed instruction (Research Report No 60)0 aImplementation of a Bayesian system for decision analysis in a p aIowa City IA: American College Testing Program1 aFerguson, R L1 aNovick, M R uhttp://mail.iacat.org/content/implementation-bayesian-system-decision-analysis-program-individually-prescribed-instruction00458nas a2200097 4500008004100000245009900041210006900140260001700209100001700226856011700243 1973 eng d00aAn interactive computer program for tailored testing based on the one-parameter logistic model0 ainteractive computer program for tailored testing based on the o aSt. Louis MO1 aReckase, M D uhttp://mail.iacat.org/content/interactive-computer-program-tailored-testing-based-one-parameter-logistic-model-000486nas a2200121 4500008004100000245009300041210006900134300000900203490000700212100001600219700001700235856011200252 1972 eng d00aIndividual intelligence testing without the examiner: reliability of an automated method0 aIndividual intelligence testing without the examiner reliability a9-140 v381 aElwood, D L1 aGriffin, H R uhttp://mail.iacat.org/content/individual-intelligence-testing-without-examiner-reliability-automated-method00445nas a2200097 4500008004100000245007500041210006900116260004600185100001300231856010300244 1972 eng d00aIndividualized testing and item characteristic curve theory (RB-72-50)0 aIndividualized testing and item characteristic curve theory RB72 aPrinceton NJ: Educational Testing Service1 aLord, FM uhttp://mail.iacat.org/content/individualized-testing-and-item-characteristic-curve-theory-rb-72-5000404nas a2200097 4500008004100000245005000041210005000091260007400141100001400215856007700229 1971 eng d00aIndividualized testing by Bayesian estimation0 aIndividualized testing by Bayesian estimation aSeattle: University of Washington, Bureau of Testing Project 0171-1771 aUrry, V W uhttp://mail.iacat.org/content/individualized-testing-bayesian-estimation00443nas a2200097 4500008004100000245004600041210004500087260012000132100001800252856007500270 1970 eng d00aIndividually tailored testing: Discussion0 aIndividually tailored testing Discussion aW. H. Holtzman, (Ed.), Computer-assisted instruction, testing, and guidance (pp.198-200). New York: Harper and Row.1 aHoltzman, W H uhttp://mail.iacat.org/content/individually-tailored-testing-discussion00336nas a2200085 4500008004100000245005600041210005600097100001400153856008300167 1969 eng d00aIndividualized assessment of differential abilities0 aIndividualized assessment of differential abilities1 aWeiss, DJ uhttp://mail.iacat.org/content/individualized-assessment-differential-abilities00463nas a2200097 4500008004100000245005500041210005100096260012100147100001600268856008100284 1969 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aR. C. Atkinson and H. A. Wilson (Eds.), Computer-assisted instruction: A book of readings. New York: Academic Press.1 aHansen, D N uhttp://mail.iacat.org/content/investigation-computer-based-science-testing-100412nas a2200109 4500008004100000245005500041210005100096260004500147100001600192700001500208856007900223 1968 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aTallahassee FL: Florida State University1 aHansen, D N1 aSchwarz, G uhttp://mail.iacat.org/content/investigation-computer-based-science-testing00440nas a2200109 4500008004100000245005500041210005100096260007100147100001600218700001500234856008100249 1968 eng d00aAn investigation of computer-based science testing0 ainvestigation of computerbased science testing aTallahassee: Institute of Human Learning, Florida State University1 aHansen, D N1 aSchwarz, G uhttp://mail.iacat.org/content/investigation-computer-based-science-testing-0