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Lim, Hwanggyu; Davey, Tim; Wells, Craig S. – Journal of Educational Measurement, 2021
This study proposed a recursion-based analytical approach to assess measurement precision of ability estimation and classification accuracy in multistage adaptive tests (MSTs). A simulation study was conducted to compare the proposed recursion-based analytical method with an analytical method proposed by Park, Kim, Chung, and Dodd and with the…
Descriptors: Adaptive Testing, Measurement, Accuracy, Classification
Jing Ma – ProQuest LLC, 2024
This study investigated the impact of scoring polytomous items later on measurement precision, classification accuracy, and test security in mixed-format adaptive testing. Utilizing the shadow test approach, a simulation study was conducted across various test designs, lengths, number and location of polytomous item. Results showed that while…
Descriptors: Scoring, Adaptive Testing, Test Items, Classification
Cai, Liuhan; Albano, Anthony D.; Roussos, Louis A. – Measurement: Interdisciplinary Research and Perspectives, 2021
Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…
Descriptors: Adaptive Testing, Test Items, Item Response Theory, Test Construction
Ramsey Lee Cardwell – ProQuest LLC, 2022
The emergence of digital-first assessments is prompting reconsideration of, and innovation in, aspects of psychometrics, test validation, and test use. Using the Duolingo English Test (DET) as an example, this three-paper series seeks to address issues concerning the estimation of classification consistency and the reporting of results for such…
Descriptors: Classification, Reliability, Language Proficiency, Computer Assisted Testing
Bao, Yu; Bradshaw, Laine – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…
Descriptors: Test Items, Selection, Adaptive Testing, 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
Liu, Shuchang; Cai, Yan; Tu, Dongbo – Journal of Educational Measurement, 2018
This study applied the mode of on-the-fly assembled multistage adaptive testing to cognitive diagnosis (CD-OMST). Several and several module assembly methods for CD-OMST were proposed and compared in terms of measurement precision, test security, and constrain management. The module assembly methods in the study included the maximum priority index…
Descriptors: Adaptive Testing, Monte Carlo Methods, Computer Security, Clinical Diagnosis
Dünya, Beyza Aksu – ProQuest LLC, 2017
This study was conducted to analyze potential item parameter drift (IPD) impact on person ability estimates and classification accuracy when drift affects an examinee sub-group. 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: Item Banks, Adaptive Testing, Computer Assisted Testing, Correlation
Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G. – Educational and Psychological Measurement, 2017
The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…
Descriptors: Testing, Performance, Prediction, Error of Measurement
Keller-Margulis, Milena; McQuillin, Samuel D.; Castañeda, Juan Javier; Ochs, Sarah; Jones, John H. – Journal of Applied School Psychology, 2018
Multitiered systems of support depend on screening technology to identify students at risk. The purpose of this study was to examine the use of a computer-adaptive test and latent class growth analysis (LCGA) to identify students at risk in reading with focus on the use of this methodology to characterize student performance in screening.…
Descriptors: At Risk Students, Multivariate Analysis, Adaptive Testing, Computer Assisted Testing