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Gorgun, Guher; Bulut, Okan – Large-scale Assessments in Education, 2023
In low-stakes assessment settings, students' performance is not only influenced by students' ability level but also their test-taking engagement. In computerized adaptive tests (CATs), disengaged responses (e.g., rapid guesses) that fail to reflect students' true ability levels may lead to the selection of less informative items and thereby…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
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Arce-Ferrer, Alvaro J.; Bulut, Okan – Journal of Experimental Education, 2019
This study investigated the performance of four widely used data-collection designs in detecting test-mode effects (i.e., computer-based versus paper-based testing). The experimental conditions included four data-collection designs, two test-administration modes, and the availability of an anchor assessment. The test-level and item-level results…
Descriptors: Data Collection, Test Construction, Test Format, Computer Assisted Testing
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Bulut, Okan; Lei, Ming; Guo, Qi – International Journal of Research & Method in Education, 2018
Item positions in educational assessments are often randomized across students to prevent cheating. However, if altering item positions results in any significant impact on students' performance, it may threaten the validity of test scores. Two widely used approaches for detecting position effects -- logistic regression and hierarchical…
Descriptors: Alternative Assessment, Disabilities, Computer Assisted Testing, Structural Equation Models
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Bulut, Okan; Kan, Adnan – Eurasian Journal of Educational Research, 2012
Problem Statement: Computerized adaptive testing (CAT) is a sophisticated and efficient way of delivering examinations. In CAT, items for each examinee are selected from an item bank based on the examinee's responses to the items. In this way, the difficulty level of the test is adjusted based on the examinee's ability level. Instead of…
Descriptors: Adaptive Testing, Computer Assisted Testing, College Entrance Examinations, Graduate Students