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Software report
Conducting simulation studies for computerized adaptive testing using SimulCAT: an instructional piece  
Kyung (Chris) Tyek Han
J Educ Eval Health Prof. 2018;15:20.   Published online August 17, 2018
DOI: https://doi.org/10.3352/jeehp.2018.15.20
  • 28,977 View
  • 244 Download
  • 7 Web of Science
  • 7 Crossref
AbstractAbstract PDFSupplementary Material
Computerized adaptive testing (CAT) technology is widely used in a variety of licensing and certification examinations administered to health professionals in the United States. Many more countries worldwide are expected to adopt CAT for their national licensing examinations for health professionals due to its reduced test time and more accurate estimation of a test-taker’s performance ability. Continuous improvements to CAT algorithms promote the stability and reliability of the results of such examinations. For this reason, conducting simulation studies is a critically important component of evaluating the design of CAT programs and their implementation. This report introduces the principles of SimulCAT, a software program developed for conducting CAT simulation studies. The key evaluation criteria for CAT simulation studies are explained and some guidelines are offered for practitioners and test developers. A step-by-step tutorial example of a SimulCAT run is also presented. The SimulCAT program supports most of the methods used for the 3 key components of item selection in CAT: the item selection criterion, item exposure control, and content balancing. Methods for determining the test length (fixed or variable) and score estimation algorithms are also covered. The simulation studies presented include output files for the response string, item use, standard error of estimation, Newton-Raphson iteration information, theta estimation, the full response matrix, and the true standard error of estimation. In CAT simulations, one condition cannot be generalized to another; therefore, it is recommended that practitioners perform CAT simulation studies in each stage of CAT development.

Citations

Citations to this article as recorded by  
  • Presidential address: improving item validity and adopting computer-based testing, clinical skills assessments, artificial intelligence, and virtual reality in health professions licensing examinations in Korea
    Hyunjoo Pai
    Journal of Educational Evaluation for Health Professions.2023; 20: 8.     CrossRef
  • Students’ perceptions of Computerised Adaptive Testing in higher education
    Proya Ramgovind, Shamola Pramjeeth
    The Independent Journal of Teaching and Learning.2023; 18(2): 109.     CrossRef
  • Preliminary Development of an Item Bank and an Adaptive Test in Mathematical Knowledge for University Students
    Fernanda Belén Ghio, Manuel Bruzzone, Luis Rojas-Torres, Marcos Cupani
    European Journal of Science and Mathematics Education.2022; 10(3): 352.     CrossRef
  • Evaluating a Computerized Adaptive Testing Version of a Cognitive Ability Test Using a Simulation Study
    Ioannis Tsaousis, Georgios D. Sideridis, Hannan M. AlGhamdi
    Journal of Psychoeducational Assessment.2021; 39(8): 954.     CrossRef
  • Exploring Counselor‐Client Agreement on Clients’ Work Capacity in Established and Consultative Dyads
    Uma Chandrika Millner, Diane Brandt, Leighton Chan, Alan Jette, Elizabeth Marfeo, Pengsheng Ni, Elizabeth Rasch, E. Sally Rogers
    Journal of Employment Counseling.2020; 57(3): 98.     CrossRef
  • Development of a Computerized Adaptive Testing for Internet Addiction
    Yong Zhang, Daxun Wang, Xuliang Gao, Yan Cai, Dongbo Tu
    Frontiers in Psychology.2019;[Epub]     CrossRef
  • Updates from 2018: Being indexed in Embase, becoming an affiliated journal of the World Federation for Medical Education, implementing an optional open data policy, adopting principles of transparency and best practice in scholarly publishing, and appreci
    Sun Huh
    Journal of Educational Evaluation for Health Professions.2018; 15: 36.     CrossRef
Review
Components of the item selection algorithm in computerized adaptive testing  
Kyung (Chris) Tyek Han
J Educ Eval Health Prof. 2018;15:7.   Published online March 24, 2018
DOI: https://doi.org/10.3352/jeehp.2018.15.7
  • 43,807 View
  • 482 Download
  • 13 Web of Science
  • 11 Crossref
AbstractAbstract PDFSupplementary Material
Computerized adaptive testing (CAT) greatly improves measurement efficiency in high-stakes testing operations through the selection and administration of test items with the difficulty level that is most relevant to each individual test taker. This paper explains the 3 components of a conventional CAT item selection algorithm: test content balancing, the item selection criterion, and item exposure control. Several noteworthy methodologies underlie each component. The test script method and constrained CAT method are used for test content balancing. Item selection criteria include the maximized Fisher information criterion, the b-matching method, the astratification method, the weighted likelihood information criterion, the efficiency balanced information criterion, and the KullbackLeibler information criterion. The randomesque method, the Sympson-Hetter method, the unconditional and conditional multinomial methods, and the fade-away method are used for item exposure control. Several holistic approaches to CAT use automated test assembly methods, such as the shadow test approach and the weighted deviation model. Item usage and exposure count vary depending on the item selection criterion and exposure control method. Finally, other important factors to consider when determining an appropriate CAT design are the computer resources requirement, the size of item pools, and the test length. The logic of CAT is now being adopted in the field of adaptive learning, which integrates the learning aspect and the (formative) assessment aspect of education into a continuous, individualized learning experience. Therefore, the algorithms and technologies described in this review may be able to help medical health educators and high-stakes test developers to adopt CAT more actively and efficiently.

Citations

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  • A shortened test is feasible: Evaluating a large-scale multistage adaptive English language assessment
    Shangchao Min, Kyoungwon Bishop
    Language Testing.2024;[Epub]     CrossRef
  • Efficiency of PROMIS MCAT Assessments for Orthopaedic Care
    Michael Bass, Scott Morris, Sheng Zhang
    Measurement: Interdisciplinary Research and Perspectives.2024; : 1.     CrossRef
  • The Effects of Different Item Selection Methods on Test Information and Test Efficiency in Computer Adaptive Testing
    Merve ŞAHİN KÜRŞAD
    Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi.2023; 14(1): 33.     CrossRef
  • Presidential address: improving item validity and adopting computer-based testing, clinical skills assessments, artificial intelligence, and virtual reality in health professions licensing examinations in Korea
    Hyunjoo Pai
    Journal of Educational Evaluation for Health Professions.2023; 20: 8.     CrossRef
  • Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures
    Conrad Harrison, Ryan Trickett, Justin Wormald, Thomas Dobbs, Przemysław Lis, Vesselin Popov, David J Beard, Jeremy Rodrigues
    Journal of Medical Internet Research.2023; 25: e47179.     CrossRef
  • Utilizing Real-Time Test Data to Solve Attenuation Paradox in Computerized Adaptive Testing to Enhance Optimal Design
    Jyun-Hong Chen, Hsiu-Yi Chao
    Journal of Educational and Behavioral Statistics.2023;[Epub]     CrossRef
  • A Context-based Question Selection Model to Support the Adaptive Assessment of Learning: A study of online learning assessment in elementary schools in Indonesia
    Umi Laili Yuhana, Eko Mulyanto Yuniarno, Wenny Rahayu, Eric Pardede
    Education and Information Technologies.2023;[Epub]     CrossRef
  • Evaluating a Computerized Adaptive Testing Version of a Cognitive Ability Test Using a Simulation Study
    Ioannis Tsaousis, Georgios D. Sideridis, Hannan M. AlGhamdi
    Journal of Psychoeducational Assessment.2021; 39(8): 954.     CrossRef
  • Developing Multistage Tests Using D-Scoring Method
    Kyung (Chris) T. Han, Dimiter M. Dimitrov, Faisal Al-Mashary
    Educational and Psychological Measurement.2019; 79(5): 988.     CrossRef
  • Conducting simulation studies for computerized adaptive testing using SimulCAT: an instructional piece
    Kyung (Chris) Tyek Han
    Journal of Educational Evaluation for Health Professions.2018; 15: 20.     CrossRef
  • Updates from 2018: Being indexed in Embase, becoming an affiliated journal of the World Federation for Medical Education, implementing an optional open data policy, adopting principles of transparency and best practice in scholarly publishing, and appreci
    Sun Huh
    Journal of Educational Evaluation for Health Professions.2018; 15: 36.     CrossRef

JEEHP : Journal of Educational Evaluation for Health Professions