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Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
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Emery-Wetherell, Meaghan; Wang, Ruoyao – Assessment & Evaluation in Higher Education, 2023
Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Cheating, Identification
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Berger, Stéphanie; Verschoor, Angela J.; Eggen, Theo J. H. M.; Moser, Urs – Journal of Educational Measurement, 2019
Calibration of an item bank for computer adaptive testing requires substantial resources. In this study, we investigated whether the efficiency of calibration under the Rasch model could be enhanced by improving the match between item difficulty and student ability. We introduced targeted multistage calibration designs, a design type that…
Descriptors: Simulation, Computer Assisted Testing, Test Items, Difficulty Level
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
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Goolsby-Cole, Cody; Bass, Sarah M.; Stanwyck, Liz; Leupen, Sarah; Carpenter, Tara S.; Hodges, Linda C. – Journal of College Science Teaching, 2023
During the pandemic, the use of question pools for online testing was recommended to mitigate cheating, exposing multitudes of science, technology, engineering, and mathematics (STEM) students across the globe to this practice. Yet instructors may be unfamiliar with the ways that seemingly small changes between questions in a pool can expose…
Descriptors: Science Instruction, Computer Assisted Testing, Cheating, STEM Education
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Zhang, Lishan; VanLehn, Kurt – Interactive Learning Environments, 2021
Despite their drawback, multiple-choice questions are an enduring feature in instruction because they can be answered more rapidly than open response questions and they are easily scored. However, it can be difficult to generate good incorrect choices (called "distractors"). We designed an algorithm to generate distractors from a…
Descriptors: Semantics, Networks, Multiple Choice Tests, Teaching Methods
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Albano, Anthony D.; Cai, Liuhan; Lease, Erin M.; McConnell, Scott R. – Journal of Educational Measurement, 2019
Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in…
Descriptors: Test Items, Computer Assisted Testing, Item Analysis, Difficulty Level
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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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Bastianello, Tamara; Brondino, Margherita; Persici, Valentina; Majorano, Marinella – Journal of Research in Childhood Education, 2023
The present contribution aims at presenting an assessment tool (i.e., the TALK-assessment) built to evaluate the language development and school readiness of Italian preschoolers before they enter primary school, and its predictive validity for the children's reading and writing skills at the end of the first year of primary school. The early…
Descriptors: Literacy, Computer Assisted Testing, Italian, Language Acquisition
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Kim, Ahyoung Alicia; Tywoniw, Rurik L.; Chapman, Mark – Language Assessment Quarterly, 2022
Technology-enhanced items (TEIs) are innovative, computer-delivered test items that allow test takers to better interact with the test environment compared to traditional multiple-choice items (MCIs). The interactive nature of TEIs offer improved construct coverage compared with MCIs but little research exists regarding students' performance on…
Descriptors: Language Tests, Test Items, Computer Assisted Testing, English (Second Language)
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Gu, Lin; Ling, Guangming; Liu, Ou Lydia; Yang, Zhitong; Li, Guirong; Kardanova, Elena; Loyalka, Prashant – Assessment & Evaluation in Higher Education, 2021
We examine the effects of computer-based versus paper-based assessment of critical thinking skills, adapted from English (in the U.S.) to Chinese. Using data collected based on a random assignment between the two modes in multiple Chinese colleges, we investigate mode effects from multiple perspectives: mean scores, measurement precision, item…
Descriptors: Critical Thinking, Tests, Test Format, Computer Assisted Testing
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Ozturk, Nagihan Boztunc; Dogan, Nuri – Educational Sciences: Theory and Practice, 2015
This study aims to investigate the effects of item exposure control methods on measurement precision and on test security under various item selection methods and item pool characteristics. In this study, the Randomesque (with item group sizes of 5 and 10), Sympson-Hetter, and Fade-Away methods were used as item exposure control methods. Moreover,…
Descriptors: Computer Assisted Testing, Item Analysis, Statistical Analysis, Comparative Analysis
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Lee, Senyung; Shin, Sun-Young – Language Assessment Quarterly, 2021
Multiple test tasks are available for assessing L2 collocation knowledge. However, few studies have investigated the characteristics of a variety of recognition and recall tasks of collocation simultaneously, and most research on L2 collocations has focused on verb-noun and adjective-noun collocations. This study investigates (1) the relative…
Descriptors: Phrase Structure, Second Language Learning, Language Tests, Recall (Psychology)
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Brinkhuis, Matthieu J. S.; Savi, Alexander O.; Hofman, Abe D.; Coomans, Frederik; van der Maas, Han L. J.; Maris, Gunter – Journal of Learning Analytics, 2018
With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion…
Descriptors: Data Analysis, Mathematics Instruction, Accuracy, Reaction Time
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Zhang, Jinming; Li, Jie – Journal of Educational Measurement, 2016
An IRT-based sequential procedure is developed to monitor items for enhancing test security. The procedure uses a series of statistical hypothesis tests to examine whether the statistical characteristics of each item under inspection have changed significantly during CAT administration. This procedure is compared with a previously developed…
Descriptors: Computer Assisted Testing, Test Items, Difficulty Level, Item Response Theory
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