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Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
Fu, Yanyan; Strachan, Tyler; Ip, Edward H.; Willse, John T.; Chen, Shyh-Huei; Ackerman, Terry – International Journal of Testing, 2020
This research examined correlation estimates between latent abilities when using the two-dimensional and three-dimensional compensatory and noncompensatory item response theory models. Simulation study results showed that the recovery of the latent correlation was best when the test contained 100% of simple structure items for all models and…
Descriptors: Item Response Theory, Models, Test Items, Simulation
Andrews-Todd, Jessica; Kerr, Deirdre – International Journal of Testing, 2019
Collaborative problem solving (CPS) has been deemed a critical twenty-first century competency for a variety of contexts. However, less attention has been given to work aimed at the assessment and acquisition of such capabilities. Recently large scale efforts have been devoted toward assessing CPS skills, but there are no agreed upon guiding…
Descriptors: Cooperative Learning, Problem Solving, Student Evaluation, Evidence Based Practice
Cui, Ying; Guo, Qi; Leighton, Jacqueline P.; Chu, Man-Wai – International Journal of Testing, 2020
This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…
Descriptors: Inferences, Artificial Intelligence, Data Analysis, Computer Assisted Testing
Aksu Dunya, Beyza – International Journal of Testing, 2018
This study was conducted to analyze potential item parameter drift (IPD) impact on person ability estimates and classification accuracy when drift affects an examinee subgroup. Using a series of simulations, three factors were manipulated: (a) percentage of IPD items in the CAT exam, (b) percentage of examinees affected by IPD, and (c) item pool…
Descriptors: Adaptive Testing, Classification, Accuracy, Computer Assisted Testing
Man, Kaiwen; Harring, Jeffery R.; Ouyang, Yunbo; Thomas, Sarah L. – International Journal of Testing, 2018
Many important high-stakes decisions--college admission, academic performance evaluation, and even job promotion--depend on accurate and reliable scores from valid large-scale assessments. However, examinees sometimes cheat by copying answers from other test-takers or practicing with test items ahead of time, which can undermine the effectiveness…
Descriptors: Reaction Time, High Stakes Tests, Test Wiseness, Cheating
Bradshaw, Laine P.; Madison, Matthew J. – International Journal of Testing, 2016
In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic…
Descriptors: Classification, Models, Simulation, Psychometrics
Sen, Sedat – International Journal of Testing, 2018
Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…
Descriptors: Item Response Theory, Comparative Analysis, Computation, Maximum Likelihood Statistics
Rutkowski, Leslie; Rutkowski, David; Zhou, Yan – International Journal of Testing, 2016
Using an empirically-based simulation study, we show that typically used methods of choosing an item calibration sample have significant impacts on achievement bias and system rankings. We examine whether recent PISA accommodations, especially for lower performing participants, can mitigate some of this bias. Our findings indicate that standard…
Descriptors: Simulation, International Programs, Adolescents, Student Evaluation