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Clements, Douglas H.; Banse, Holland; Sarama, Julie; Tatsuoka, Curtis; Joswick, Candace; Hudyma, Aaron; Van Dine, Douglas W.; Tatsuoka, Kikumi K. – Mathematical Thinking and Learning: An International Journal, 2022
Researchers often develop instruments using correctness scores (and a variety of theories and techniques, such as Item Response Theory) for validation and scoring. Less frequently, observations of children's strategies are incorporated into the design, development, and application of assessments. We conducted individual interviews of 833…
Descriptors: Item Response Theory, Computer Assisted Testing, Test Items, Mathematics Tests
Jiang, Yang; Gong, Tao; Saldivia, Luis E.; Cayton-Hodges, Gabrielle; Agard, Christopher – Large-scale Assessments in Education, 2021
In 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to…
Descriptors: Data Use, Learning Analytics, Test Items, Measurement
OECD Publishing, 2019
Log files from computer-based assessment can help better understand respondents' behaviours and cognitive strategies. Analysis of timing information from Programme for the International Assessment of Adult Competencies (PIAAC) reveals large differences in the time participants take to answer assessment items, as well as large country differences…
Descriptors: Adults, Computer Assisted Testing, Test Items, Reaction Time
Jewsbury, Paul A.; van Rijn, Peter W. – Journal of Educational and Behavioral Statistics, 2020
In large-scale educational assessment data consistent with a simple-structure multidimensional item response theory (MIRT) model, where every item measures only one latent variable, separate unidimensional item response theory (UIRT) models for each latent variable are often calibrated for practical reasons. While this approach can be valid for…
Descriptors: Item Response Theory, Computation, Test Items, Adaptive Testing
Moon, Jung Aa; Sinharay, Sandip; Keehner, Madeleine; Katz, Irvin R. – International Journal of Testing, 2020
The current study examined the relationship between test-taker cognition and psychometric item properties in multiple-selection multiple-choice and grid items. In a study with content-equivalent mathematics items in alternative item formats, adult participants' tendency to respond to an item was affected by the presence of a grid and variations of…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Test Wiseness, Psychometrics
Susanti, Yuni; Tokunaga, Takenobu; Nishikawa, Hitoshi – Research and Practice in Technology Enhanced Learning, 2020
The present study focuses on the integration of an automatic question generation (AQG) system and a computerised adaptive test (CAT). We conducted two experiments. In the first experiment, we administered sets of questions to English learners to gather their responses. We further used their responses in the second experiment, which is a…
Descriptors: Computer Assisted Testing, Test Items, Simulation, English Language Learners
Kuang, Huan; Sahin, Fusun – Large-scale Assessments in Education, 2023
Background: Examinees may not make enough effort when responding to test items if the assessment has no consequence for them. These disengaged responses can be problematic in low-stakes, large-scale assessments because they can bias item parameter estimates. However, the amount of bias, and whether this bias is similar across administrations, is…
Descriptors: Test Items, Comparative Analysis, Mathematics Tests, Reaction Time
Selcuk Acar; Denis Dumas; Peter Organisciak; Kelly Berthiaume – Grantee Submission, 2024
Creativity is highly valued in both education and the workforce, but assessing and developing creativity can be difficult without psychometrically robust and affordable tools. The open-ended nature of creativity assessments has made them difficult to score, expensive, often imprecise, and therefore impractical for school- or district-wide use. To…
Descriptors: Thinking Skills, Elementary School Students, Artificial Intelligence, Measurement Techniques
Wolkowitz, Amanda A.; Foley, Brett P.; Zurn, Jared – Journal of Applied Testing Technology, 2021
As assessments move from traditional paper-pencil administration to computer-based administration, many testing programs are incorporating alternative item types (AITs) into assessments with the goals of measuring higher-order thinking, offering insight into problem-solving, and representing authentic real-world tasks. This paper explores multiple…
Descriptors: Psychometrics, Alternative Assessment, Computer Assisted Testing, Test Items
Alexander James Kwako – ProQuest LLC, 2023
Automated assessment using Natural Language Processing (NLP) has the potential to make English speaking assessments more reliable, authentic, and accessible. Yet without careful examination, NLP may exacerbate social prejudices based on gender or native language (L1). Current NLP-based assessments are prone to such biases, yet research and…
Descriptors: Gender Bias, Natural Language Processing, Native Language, Computational Linguistics
Cui, Zhongmin; Liu, Chunyan; He, Yong; Chen, Hanwei – Journal of Educational Measurement, 2018
Allowing item review in computerized adaptive testing (CAT) is getting more attention in the educational measurement field as more and more testing programs adopt CAT. The research literature has shown that allowing item review in an educational test could result in more accurate estimates of examinees' abilities. The practice of item review in…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Test Wiseness
Li, Jie; van der Linden, Wim J. – Journal of Educational Measurement, 2018
The final step of the typical process of developing educational and psychological tests is to place the selected test items in a formatted form. The step involves the grouping and ordering of the items to meet a variety of formatting constraints. As this activity tends to be time-intensive, the use of mixed-integer programming (MIP) has been…
Descriptors: Programming, Automation, Test Items, Test Format
Arslan, Burcu; Jiang, Yang; Keehner, Madeleine; Gong, Tao; Katz, Irvin R.; Yan, Fred – Educational Measurement: Issues and Practice, 2020
Computer-based educational assessments often include items that involve drag-and-drop responses. There are different ways that drag-and-drop items can be laid out and different choices that test developers can make when designing these items. Currently, these decisions are based on experts' professional judgments and design constraints, rather…
Descriptors: Test Items, Computer Assisted Testing, Test Format, Decision Making
Luo, Xiao; Wang, Xinrui – International Journal of Testing, 2019
This study introduced dynamic multistage testing (dy-MST) as an improvement to existing adaptive testing methods. dy-MST combines the advantages of computerized adaptive testing (CAT) and computerized adaptive multistage testing (ca-MST) to create a highly efficient and regulated adaptive testing method. In the test construction phase, multistage…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Construction, Psychometrics
Lin, Chuan-Ju; Chang, Hua-Hua – Educational and Psychological Measurement, 2019
For 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…
Descriptors: Test Items, Selection Criteria, Computer Assisted Testing, Adaptive Testing

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