Gotowe bibliografie tematyczne / Computer adaptive testing (CAT)

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Gotowa bibliografia na temat „Computer adaptive testing (CAT)”

Autor: Grafiati
Data publikacji: 3 czerwca 2025
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Computer adaptive testing (CAT)"

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Gotskaya, I. B., and V. I. Snegurova. "Model of a Computer Adaptive Learning Testing System." Pushkin Leningrad State University Journal 2 (2025): 174–87. https://doi.org/10.35231/18186653_2025_2_174.

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Introduction. The creation of a conceptually new CAT model was based on the results of theoretical and experimental studies by Russian (V. A. Veksler, P. P. Dyachuk, V. S. Dobryak, T. M. Zubkova, A. R. Kochura, M. S. Mazorchuk, I. P. Peregudova, L. F. Tagirova, etc.) and foreign researchers (M. V. Brus, A. J. Martin, G. Lazendic, S. L. Zahrebelnyi). The analysis of these studies revealed three established approaches to adaptation used in most CAT systems (variation of the number, difficulty level, and time for completing test tasks). However, the problem of individual CAT customization remaine
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Carlson, Randal D. "Computer Adaptive Testing: A Shift in the Evaluation Paradigm." Journal of Educational Technology Systems 22, no. 3 (1994): 213–24. http://dx.doi.org/10.2190/qp36-wv9l-att3-fywk.

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Evaluating and/or testing individuals is utilized in a wide range of instructional situations. This article reviews the development and use of mass testing procedures commonly employed to evaluate large groups of relatively homogeneous individuals and suggests computer adaptive testing (CAT) as a viable alternative to conventional testing in many situations. The CAT process is outlined and briefly described.
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Chalhoub–Deville, Micheline, and Craig Deville. "COMPUTER ADAPTIVE TESTING IN SECOND LANGUAGE CONTEXTS." Annual Review of Applied Linguistics 19 (January 1999): 273–99. http://dx.doi.org/10.1017/s0267190599190147.

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The widespread accessibility to large, networked computer labs at educational sites and commercial testing centers, coupled with fast-paced advances in both computer technology and measurement theory, along with the availability of off-the-shelf software for test delivery, all help to make the computerized assessment of individuals more efficient and accurate than assessment using traditional paper-and-pencil (P&P) tests. Computer adaptive testing (CAT) is a form of computerized assessment that has achieved a strong foothold in licensure and certification testing and is finding greater app
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Kimura, Tetsuo. "The impacts of computer adaptive testing from a variety of perspectives." Journal of Educational Evaluation for Health Professions 14 (May 29, 2017): 12. http://dx.doi.org/10.3352/jeehp.2017.14.12.

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Computer adaptive testing (CAT) is a kind of tailored testing, in that it is a form of computer-based testing that is adaptive to each test-taker’s ability level. In this review, the impacts of CAT are discussed from different perspectives in order to illustrate crucial points to keep in mind during the development and implementation of CAT. Test developers and psychometricians often emphasize the efficiency and accuracy of CAT in comparison to traditional linear tests. However, many test-takers report feeling discouraged after taking CATs, and this feeling can reduce learning self-efficacy an
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Ayanwale, Musa Adekunle, and Mdutshekelwa Ndlovu. "Transition from computer-based testing of national benchmark tests to adaptive testing: Robust application of fourth industrial revolution tools." Cypriot Journal of Educational Sciences 17, no. 9 (2022): 3327–43. http://dx.doi.org/10.18844/cjes.v17i9.7124.

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In 2020, the COVID-19 pandemic strongly affected all sectors, including education. Across the globe, governments enacted policies restricting people's movement, affecting the educational assessment industry. During the lockdown, South Africa's National Benchmark Tests (NBTs) were cancelled. In contrast to paper-pencil and linear tests deployed for NBTs, computer-adaptive testing (CAT) is a modern alternative. CAT technology is widely used for licensing and certification exams in most developed nations. CAT is expected to be used by many educational assessment companies in sub-Saharan Africa fo
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Imawan, Okky Riswandha, Heri Retnawati, Haryanto, and Raoda Ismail. "The challenges of implementing computerized adaptive testing in Indonesia." Journal of Education and e-Learning Research 12, no. 2 (2025): 124–44. https://doi.org/10.20448/jeelr.v12i2.6677.

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This study explores the challenges of implementing computerized adaptive testing (CAT) for mathematics assessment among prospective elementary school teachers in Indonesia. It aims to describe (1) assessment practices of mathematics lecturers and (2) challenges in adopting CAT. Using a qualitative phenomenological approach, data were collected from 17 mathematics lecturers across Indonesia through questionnaires followed by in-depth interviews with four lecturers unfamiliar with or struggling to use CAT. Findings indicate that paper-and-pencil tests and computer- based testing (CBT) dominate u
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Ramgovind, Proya, and Shamola Pramjeeth. "Students’ perceptions of Computerised Adaptive Testing in higher education." Independent Journal of Teaching and Learning 18, no. 2 (2023): 109–26. http://dx.doi.org/10.17159/ijtl.v18i2.17314.

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The COVID-19 pandemic has forced higher education institutions (HEIs) to re-look at their assessment strategy as learning, development, and engagement move more fluidly into the online arena. The purpose of this research was to investigate students' academic and personal perceptions of computer adaptive testing (CAT) in higher education to understand students’ confidence in adopting CAT. Using a quantitative descriptive research design, an online questionnaire was administered to students at private and public HEIs in South Africa, with 600 respondents. The study found that the students were c
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Lunz, Mary E., and Betty Bergstrom. "Computerized Adaptive Testing: Tracking Candidate Response Patterns." Journal of Educational Computing Research 13, no. 2 (1995): 151–62. http://dx.doi.org/10.2190/gnb7-5hq0-gd8m-p0b2.

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Computerized adaptive testing (CAT) uses a computer algorithm to construct and score the best possible individualized or tailored tests for each candidate. The computer also provides an absolute record of all responses and changes to responses, as well as their effects on candidate performance. The detail of the data from computerized adaptive tests makes it possible to track initial responses and response alterations, and their effect on candidate estimated ability measures, as well as the statistical performance of the examination. The purpose of this study was to track the effect of candida
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Jing, Yong Jun, Xin Li, and Tian Hua Liu. "Using Maximum Information Selection Strategy to Computer Adaptive Test." Advanced Materials Research 1022 (August 2014): 282–85. http://dx.doi.org/10.4028/www.scientific.net/amr.1022.282.

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As psychology, education measure theory and with the combination of computer technology of continuous research and development, based on Computer Adaptive Test (CAT) become a new type of test form. Based on the analysis and state the topic of CAT theory and Maximum Information Selection Strategy (MISS), the method of maximum information selection strategy in the key issues in an adaptive testing system solutions is discussed. The effectiveness of the solution method which this topic given is proved by experiment.
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Oladele, Jumoke I., Mdutshekelwa Ndlovu, and Erica D. Spangenberg. "Simulated computer adaptive testing method choices for ability estimation with empirical evidence." International Journal of Evaluation and Research in Education (IJERE) 11, no. 3 (2022): 1392. http://dx.doi.org/10.11591/ijere.v11i3.21986.

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<p><span lang="EN-US">Computer adaptive testing (CAT) is a technological advancement for educational assessments that requires thorough feasibility studies through computer simulations to ensure strong testing foundations. This advancement is especially germane in Africa being adopters of technology, and this should not be done blindly without empirical evidence. A quasi-experimental design was adopted for this study to establish methodological choices for CAT ability estimation. Five thousand candidates were simulated with 100 items simulate through the three-parameter logistic mo
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Rozprawy doktorskie na temat "Computer adaptive testing (CAT)"

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Lee, Toby. "Optimizing CAT-ASVAB item selection using form assembly techniques." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Jun%5FLee.pdf.

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Brown, Reagan. "The Development of a Computer Adaptive Test Of the Five Factor Model of Personality: Applications and Extensions." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/30575.

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Although not universally accepted, much of the field has converged upon the Five Factor Model (FFM) of personality as constituting a comprehensive taxonomy of normal personality functioning. A weakness common to all personality inventories is excessive length, which can result in examinee fatigue, and ultimately, poor data quality. Computer adaptive testing offers a solution to the test fatigue problem by administering only the items that are informative for that examinee on a given scale. A new test based upon the FFM of normal personality administered in a computer adaptive fashion was co
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Kuo, Fei-Ching. "On adaptive random testing." Australasian Digital Thesis Program, 2006. http://adt.lib.swin.edu.au/public/adt-VSWT20061109.091517.

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Thesis (Ph.D) - Swinburne University of Technology, Faculty of Information & Communication Technologies, 2006.<br>A thesis submitted for the degree of PhD, Faculty of Information and Communication Technologies, Swinburne University of Technology, 2006. Typescript. Bibliography: p. 126-133.
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Kuo, Fei-Ching, and n/a. "On adaptive random testing." Swinburne University of Technology, 2006. http://adt.lib.swin.edu.au./public/adt-VSWT20061109.091517.

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Adaptive random testing (ART) has been proposed as an enhancement to random testing for situations where failure-causing inputs are clustered together. The basic idea of ART is to evenly spread test cases throughout the input domain. It has been shown by simulations and empirical analysis that ART frequently outperforms random testing. However, there are some outstanding issues on the cost-effectiveness and practicality of ART, which are the main foci of this thesis. Firstly, this thesis examines the basic factors that have an impact on the faultdetection effectiveness of adaptive random testi
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Fielder, Patrick J. (Patrick Joseph). "A Comparison of the Effectiveness of Computer Adaptive Testing and Computer Administered Testing." Thesis, University of North Texas, 1995. https://digital.library.unt.edu/ark:/67531/metadc279192/.

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The problem with which this study is concerned is determining the effectiveness of a computer adaptive test as compared to the effectiveness of using the entire test. The study has a twofold purpose. The first is to determine whether the two test versions generate equivalent scores, despite being of different lengths. The second is to determine whether the difference in time needed to take the computer adaptive test is significantly shorter than the computer administered full test.
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Towey, David Peter. "Studies of different variations of Adaptive Random Testing." Thesis, View the Table of Contents & Abstract, 2006. http://sunzi.lib.hku.hk/hkuto/record/B3551212X.

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Shah, Anuj Ramesh. "Web-CAT: A Web-based Center for Automated Testing." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/33109.

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The fundamentals of software testing and related activities are often elusive in undergraduate curricula. A direct consequence of the lack of software testing efforts during education is the huge losses suffered by the software industry when applications are not sufficiently tested. Software practitioners have exhorted faculty members and institutions to teach more software testing in universities. The purpose of this research is to provide answers to the needs of such practitioners and introduce software-testing activities throughout the curriculum. The most important goal is to introduce sof
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Liu, Ning Lareina. "A study on improving adaptive random testing." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36428061.

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Liu, Ning Lareina, and 劉寧. "A study on improving adaptive random testing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36428061.

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Arafeen, Md Junaid. "Adaptive Regression Testing Strategy: An Empirical Study." Thesis, North Dakota State University, 2012. https://hdl.handle.net/10365/26525.

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When software systems evolve, different amounts of code modifications can be involved in different versions. These factors can affect the costs and benefits of regression testing techniques, and thus, there may be no single regression testing technique that is the most cost-effective technique to use on every version. To date, many regression testing techniques have been proposed, but no research has been done on the problem of helping practitioners systematically choose appropriate techniques on new versions as systems evolve. To address this problem, we propose adaptive regression testing (A
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Książki na temat "Computer adaptive testing (CAT)"

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Liu, Mei. The impact of item location effects on ability estimation in CAT: A simulation study. Law School Admission Council, 2006.

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Meijer, Rob R. Simple nonparametric checks for model data fit in CAT. Law School Admission Council, 2005.

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Martinson, Thomas H. Master the GRE CAT 2003. 2nd ed. Peterson's, 2002.

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(Firm), Peterson's, ed. Master the GRE CAT 2004. Peterson's, 2003.

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Meijer, Rob R. Investigating the quality of items in CAT using nonparametric IRT. Law School Admission Council, 2004.

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Meijer, Rob R. Exploring new methods to detect person misfit in CAT. Law School Admission Council, 2006.

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Meijer, Rob R. Some new methods to detect person fit in CAT. Law School Admission Council, 1999.

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Yi, Qing. Effects of scale transformation and test termination rule on the precision of ability estimates in CAT. ACT, Inc., 2000.

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Meijer, Rob R. Using patterns of summed scores in paper-and-pencil tests and CAT to detect misfitting item score patterns. Law School Admission Council, 2005.

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Yi, Qing. Simulating nonmodel-fitting responses in a CAT environment. ACT, Inc., 1998.

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Części książek na temat "Computer adaptive testing (CAT)"

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van der Ark, L. Andries, and Niels Smits. "Computerized Adaptive Testing Without IRT for Flexible Measurement and Prediction." In Essays on Contemporary Psychometrics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-10370-4_19.

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AbstractIn education, testing procedures can be lengthy. The long duration takes up precious time and affects the quality of responses, possibly resulting in a biased diagnosis or wrong treatment. The problem can be reduced using computer adaptive testing (CAT). However, three issues prevent the use of traditional CAT: (1) the type of tests and questionnaires we focus on do not allow for the construction of large item banks, (2) the test data are usually not (approximately) unidimensional, and (3) the aim of the researchers may not only be measurement but also prediction. We propose a flexible
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Ek, Alexander, Michelle Blom, Philip B. Stark, Peter J. Stuckey, and Damjan Vukcevic. "Improving the Computational Efficiency of Adaptive Audits of IRV Elections." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-72244-8_3.

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AbstractAWAIRE is one of two extant methods for conducting risk-limiting audits of instant-runoff voting (IRV) elections. In principle AWAIRE can audit IRV contests with any number of candidates, but the original implementation incurred memory and computation costs that grew superexponentially with the number of candidates. This paper improves the algorithmic implementation of AWAIRE in three ways that make it practical to audit IRV contests with 55 candidates, compared to the previous 6 candidates. First, rather than trying from the start to rule out all candidate elimination orders that prod
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Segall, Daniel O. "Equating the CAT-ASVAB." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-020.

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Sands, W. A., and Brian K. Waters. "Introduction to ASVAB and CAT." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-001.

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McBride, James R. "Dissemination of CAT-ASVAB technology." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-026.

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Segall, Daniel O., Kathleen E. Moreno, Bruce M. Bloxom, and Rebecca D. Hetter. "Psychometric procedures for administering CAT-ASVAB." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-013.

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Hetter, Rebecca D., and J. Bradford Sympson. "Item exposure control in CAT-ASVAB." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-014.

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Moreno, Kathleen E. "CAT-ASVAB operational test and evaluation." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-021.

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Wise, Lauress L., Linda T. Curran, and James R. McBride. "CAT-ASVAB cost and benefit analyses." In Computerized adaptive testing: From inquiry to operation. American Psychological Association, 1997. http://dx.doi.org/10.1037/10244-024.

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Luecht, Richard M., and Ronald J. Nungester. "Computer-Adaptive Sequential Testing." In Computerized Adaptive Testing: Theory and Practice. Springer Netherlands, 2000. http://dx.doi.org/10.1007/0-306-47531-6_6.

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Streszczenia konferencji na temat "Computer adaptive testing (CAT)"

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Kennerley, Mikhail, Jian-Gang Wang, Bharadwaj Veeravalli, and Robby T. Tan. "CAT: Exploiting Inter-Class Dynamics for Domain Adaptive Object Detection." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01565.

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Pandy, Gokul, Vigneshwaran Jagadeesan Pugazhenthi, Baskaran Jeyarajan, and Aravindhan Murugan. "Advancing Robotics Testing: A Novel Framework for Adaptive and Scalable Evaluation." In 2025 17th International Conference on Computer and Automation Engineering (ICCAE). IEEE, 2025. https://doi.org/10.1109/iccae64891.2025.10980524.

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Zheng, Ziyue, Xiangchen Meng, and Yangdi Lyu. "APE-FV: Concolic Testing for RTL Functional Verification Using Adaptive Path Exploration." In 2024 IEEE 42nd International Conference on Computer Design (ICCD). IEEE, 2024. https://doi.org/10.1109/iccd63220.2024.00064.

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Chennareddy, Srihith, and Vamshi Krishna Appala. "Optimizing AI Model Training Costs with Stratified Sampling and Self-Adaptive Testing." In 2025 3rd International Conference on Advancement in Computation & Computer Technologies (InCACCT). IEEE, 2025. https://doi.org/10.1109/incacct65424.2025.11011465.

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Jin, Yonghe, Wanru Chen, Ling Hu, Yifan Zhang, and Yuyang Chen. "Application and research of adaptive architecture data acquisition technology in metrology and testing projects." In 2024 International Seminar on Artificial Intelligence, Computer Technology and Control Engineering (ACTCE). IEEE, 2024. https://doi.org/10.1109/actce65085.2024.00063.

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Msayer, Mohamed El, Es-Saâdia Aoula, and Bouchra Bouihi. "Artificial intelligence in computerized adaptive testing to assess the cognitive performance of students: A Systematic Review." In 2024 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, 2024. http://dx.doi.org/10.1109/iscv60512.2024.10620092.

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Karahoca, Adem, Dilek Karahoca, and Furkan Ince. "ANFIS supported question classification in computer adaptive testing (CAT)." In 2009 Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control. IEEE, 2009. http://dx.doi.org/10.1109/icsccw.2009.5379498.

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Orabi, Farida, Essam Kosba, and Walid AbdelMoez. "A Modified Multinomial Platform Architecture for Computer Adaptive Testing (CAT)." In 2018 28th International Conference on Computer Theory and Applications (ICCTA). IEEE, 2018. http://dx.doi.org/10.1109/iccta45985.2018.9499105.

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Razmadze, Simon. "Scoring the Outcomes of 1-3-3 Multistage Model of Computerized Adaptive Testing." In International Conference on Computer Science and Information Technologies. The University of Georgia, 2024. https://doi.org/10.62343/csit.2024.16.

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The paper presented considers the ordering method of outcome set for multi-stage testing (MST) of 1-3-3 model. The ordering method of outcome set is used for the estimation of results of computerized adaptive testing (CAT). This method is not tied to a specific testing procedure. Acknowledgment of this is its usage for the 1-3-3 model, which is described in the paper. To sort the set of testing outcomes the function-criteria described in the initial article are used here and a comparative analysis of obtained results is performed. The ordered outcome set is estimated by a hundred-point system
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Koskey, Kristin, Dara Bright, Katrina Struloeff, et al. "ADAPTATION OF THE DELPHI TECHNIQUE IN THE DEVELOPMENT OF ASSESSMENTS OF PROBLEM-SOLVING IN COMPUTER ADAPTIVE TESTING ENVIRONMENTS (DEAP-CAT)." In 14th annual International Conference of Education, Research and Innovation. IATED, 2021. http://dx.doi.org/10.21125/iceri.2021.2142.

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Raporty organizacyjne na temat "Computer adaptive testing (CAT)"

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Divgi, D. R. On some Issues in the Accelerated CAT-ASVAB (Computerized Adaptive Testing-Armed Services Vocational Aptitude Battery) Project. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada178558.

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Divgi, D. R. Dimensionality of the Math Knowledge Item Pool for the Accelerated CAT- ASVAB (Computerized Adaptive Testing-Armed Services Vocational Aptitude Battery) Project. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada194109.

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Divgi, D. R. Determining the Sensitivity of CAT-ASVAB (Computerized Adaptive Testing- Armed Services Vocational Aptitude Battery) Scores to Changes in Item Response Curves with the Medium of Administration. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada175507.

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Baete, Christophe, and Keith Parker. PR405-213601-R04 Validation of Digital Twins for Monitoring, Optimization, and Compliance of CP Systems. Pipeline Research Council International, Inc. (PRCI), 2023. http://dx.doi.org/10.55274/r0012254.

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The digital twin used in this research is a mechanistic (or deterministic) computer model that represents the cathodic protection behavior of a pipeline network. The model is calibrated based on field data such that it mimics the real-world behavior of the pipeline. The objective of this research is to validate the accuracy of the digital twin model on three industry cases. First, the sensitivity of the independent variables (soil, coating and cathodic protection properties) that are the inputs of the digital twin was investigated during a literature study, a lab and field-based modeling on a
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Możesz być także zainteresowany rozszerzonymi bibliografiami na temat „Computer adaptive testing (CAT)” dla poszczególnych typów źródeł:
Artykuły w czasopismach Rozprawy doktorskie Książki
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Do bibliografii