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Senel, Selma; Kutlu, Ömer – European Journal of Special Needs Education, 2018
This paper examines listening comprehension skills of visually impaired students (VIS) using computerised adaptive testing (CAT) and reader-assisted paper-pencil testing (raPPT) and student views about them. Explanatory mixed method design was used in this study. Sample is comprised of 51 VIS, in 7th and 8th grades. 9 of these students were…
Descriptors: Computer Assisted Testing, Adaptive Testing, Visual Impairments, Student Attitudes
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Leroux, Audrey J.; Dodd, Barbara G. – Journal of Experimental Education, 2016
The current study compares the progressive-restricted standard error (PR-SE) exposure control method with the Sympson-Hetter, randomesque, and no exposure control (maximum information) procedures using the generalized partial credit model with fixed- and variable-length CATs and two item pools. The PR-SE method administered the entire item pool…
Descriptors: Computer Assisted Testing, Adaptive Testing, Comparative Analysis, Error of Measurement
Yang, Lihong – ProQuest LLC, 2016
In recent years, the multistage adaptive test (MST) has gained increasing popularity in the field of educational measurement and operational testing. MST refers to a test in which pre-constructed sets of items are administered adaptively and are scored as a unit (Hendrickson, 2007). As a special case of Computerized Adaptive Testing (CAT), a MST…
Descriptors: Item Banks, Computer Assisted Testing, Adaptive Testing, Test Construction
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Luo, Xin; Reckase, Mark D.; He, Wei – AERA Online Paper Repository, 2016
While dichotomous item dominates the application of computerized adaptive testing (CAT), polytomous item and set-based item hold promises for being incorporated in CAT. However, how to assemble a CAT containing mixed item formats is challenging. This study investigated: (1) how the mixed CAT works compared with the dichotomous-item-based CAT; (2)…
Descriptors: Test Items, Test Format, Computer Assisted Testing, Adaptive Testing
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Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
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Lin, Yin; Brown, Anna – Educational and Psychological Measurement, 2017
A fundamental assumption in computerized adaptive testing is that item parameters are invariant with respect to context--items surrounding the administered item. This assumption, however, may not hold in forced-choice (FC) assessments, where explicit comparisons are made between items included in the same block. We empirically examined the…
Descriptors: Personality Measures, Measurement Techniques, Context Effect, Test Items
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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
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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
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Sun, Bo; Zhu, Yunzong; Xiao, Yongkang; Xiao, Rong; Wei, Yungang – IEEE Transactions on Learning Technologies, 2019
In recent years, computerized adaptive testing (CAT) has gained popularity as an important means to evaluate students' ability. Assigning tags to test questions is crucial in CAT. Manual tagging is widely used for constructing question banks; however, this approach is time-consuming and might lead to consistency issues. Automatic question tagging,…
Descriptors: Computer Assisted Testing, Student Evaluation, Test Items, Multiple Choice Tests
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Hsu, Chia-Ling; Wang, Wen-Chung – Journal of Educational Measurement, 2015
Cognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent…
Descriptors: Computer Assisted Testing, Adaptive Testing, Models, Cognitive Measurement
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Soland, James – Applied Measurement in Education, 2018
This study estimated male-female and Black-White achievement gaps without accounting for low test motivation, then compared those estimates to ones that used several approaches to addressing rapid guessing. Researchers investigated two issues: (1) The differences in rates of rapid guessing across subgroups and (2) How much achievement gap…
Descriptors: Guessing (Tests), Achievement Gap, Student Motivation, Learner Engagement
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Navarro, Juan-José; Mourgues-Codern, Catalina V. – Journal of Cognitive Education and Psychology, 2018
The development of novel educational assessment models founded on item response theory (IRT), as well as software tools designed to implement these models, has contributed to the surge in computerized adaptive tests (CATs). The distinguishing characteristic of CATs is that the sequence of items on a test progressively adapts to the performance…
Descriptors: Reading Processes, Computer Assisted Testing, Adaptive Testing, Item Response Theory
Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki – International Association for Development of the Information Society, 2015
An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…
Descriptors: Adaptive Testing, Bayesian Statistics, Networks, Computer Assisted Instruction
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Van Norman, Ethan R.; Nelson, Peter M.; Parker, David C. – School Psychology Quarterly, 2017
Computer adaptive tests (CATs) hold promise to monitor student progress within multitiered systems of support. However, the relationship between how long and how often data are collected and the technical adequacy of growth estimates from CATs has not been explored. Given CAT administration times, it is important to identify optimal data…
Descriptors: Computer Assisted Testing, Progress Monitoring, Grade 4, Grade 5
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Robin, Frédéric; Bejar, Isaac; Liang, Longjuan; Rijmen, Frank – ETS Research Report Series, 2016
Exploratory and confirmatory factor analyses of domestic data from the" GRE"® revised General Test, introduced in 2011, were conducted separately for the verbal (VBL) and quantitative (QNT) reasoning measures to evaluate the unidimensionality and local independence assumptions required by item response theory (IRT). Results based on data…
Descriptors: College Entrance Examinations, Graduate Study, Verbal Tests, Mathematics Tests
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