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Kim, Rae Yeong; Yoo, Yun Joo – Journal of Educational Measurement, 2023
In cognitive diagnostic models (CDMs), a set of fine-grained attributes is required to characterize complex problem solving and provide detailed diagnostic information about an examinee. However, it is challenging to ensure reliable estimation and control computational complexity when The test aims to identify the examinee's attribute profile in a…
Descriptors: Models, Diagnostic Tests, Adaptive Testing, Accuracy
Hyo Jeong Shin; Christoph König; Frederic Robin; Andreas Frey; Kentaro Yamamoto – Journal of Educational Measurement, 2025
Many international large-scale assessments (ILSAs) have switched to multistage adaptive testing (MST) designs to improve measurement efficiency in measuring the skills of the heterogeneous populations around the world. In this context, previous literature has reported the acceptable level of model parameter recovery under the MST designs when the…
Descriptors: Robustness (Statistics), Item Response Theory, Adaptive Testing, Test Construction
Matayoshi, Jeffrey; Cosyn, Eric; Uzun, Hasan – International Journal of Artificial Intelligence in Education, 2021
Many recent studies have looked at the viability of applying recurrent neural networks (RNNs) to educational data. In most cases, this is done by comparing their performance to existing models in the artificial intelligence in education (AIED) and educational data mining (EDM) fields. While there is increasing evidence that, in many situations,…
Descriptors: Artificial Intelligence, Data Analysis, Student Evaluation, Adaptive Testing
Carol Eckerly; Yue Jia; Paul Jewsbury – ETS Research Report Series, 2022
Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Scoring
Wang, Wenhao; Kingston, Neal M.; Davis, Marcia H.; Tiemann, Gail C.; Tonks, Stephen; Hock, Michael – Educational Measurement: Issues and Practice, 2021
Adaptive tests are more efficient than fixed-length tests through the use of item response theory; adaptive tests also present students questions that are tailored to their proficiency level. Although the adaptive algorithm is straightforward, developing a multidimensional computer adaptive test (MCAT) measure is complex. Evidence-centered design…
Descriptors: Evidence Based Practice, Reading Motivation, Adaptive Testing, Computer Assisted Testing
Nixi Wang – ProQuest LLC, 2022
Measurement errors attributable to cultural issues are complex and challenging for educational assessments. We need assessment tests sensitive to the cultural heterogeneity of populations, and psychometric methods appropriate to address fairness and equity concerns. Built on the research of culturally responsive assessment, this dissertation…
Descriptors: Culturally Relevant Education, Testing, Equal Education, Validity
Andrich, David; Marais, Ida – Journal of Educational Measurement, 2018
Even though guessing biases difficulty estimates as a function of item difficulty in the dichotomous Rasch model, assessment programs with tests which include multiple-choice items often construct scales using this model. Research has shown that when all items are multiple-choice, this bias can largely be eliminated. However, many assessments have…
Descriptors: Multiple Choice Tests, Test Items, Guessing (Tests), Test Bias
Aybek, Eren Can; Demirtasli, R. Nukhet – International Journal of Research in Education and Science, 2017
This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
Albacete, Patricia; Silliman, Scott; Jordan, Pamela – Grantee Submission, 2017
Intelligent tutoring systems (ITS), like human tutors, try to adapt to student's knowledge level so that the instruction is tailored to their needs. One aspect of this adaptation relies on the ability to have an understanding of the student's initial knowledge so as to build on it, avoiding teaching what the student already knows and focusing on…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Multiple Choice Tests, Computer Assisted Testing
Hauk, Shandy; Matlen, Bryan; Thomas, Larry – Grantee Submission, 2017
A variety of computerized interactive learning platforms exist. Most include instructional supports in the form of problem sets. Feedback to users ranges from a single word like "Correct!" to offers of hints and partially- to fully-worked examples. Behind-the-scenes design of systems varies as well--from static dictionaries of problems…
Descriptors: Community Colleges, Algebra, Web Based Instruction, Randomized Controlled Trials

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