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Beatriz Campana – ProQuest LLC, 2024
Throughout the years, United States education reform has sought to target the most disadvantaged students. Nonetheless, during this same period, proficiency rate disparities seem to have emerged among student subgroups. This study was designed to find ways for school districts to begin closing the achievement gaps between student subgroups,…
Descriptors: Academic Achievement, Achievement Gap, English Language Learners, Standardized Tests
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Philip M. Newton; Keioni Essex – Journal of Academic Ethics, 2024
Academic misconduct is a threat to the validity and reliability of online examinations, and media reports suggest that misconduct spiked dramatically in higher education during the emergency shift to online exams caused by the COVID-19 pandemic. This study reviewed survey research to determine how common it is for university students to admit…
Descriptors: Cheating, Tests, Electronic Learning, COVID-19
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Qutaiba I. Ali – Discover Education, 2024
This paper contributes to the ongoing efforts aimed at enhancing Outcome-Based Education (OBE) assessment methodologies by addressing some critical gaps and exploring new solutions. Our work focuses on two main areas: firstly, this study proposes an improved assessment method for OBE. It refines traditional approaches by classifying course…
Descriptors: Outcome Based Education, Evaluation Methods, Student Evaluation, Artificial Intelligence
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Stefan Ruseti; Ionut Paraschiv; Mihai Dascalu; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Automated Essay Scoring (AES) is a well-studied problem in Natural Language Processing applied in education. Solutions vary from handcrafted linguistic features to large Transformer-based models, implying a significant effort in feature extraction and model implementation. We introduce a novel Automated Machine Learning (AutoML) pipeline…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essays
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Lahza, Hatim; Smith, Tammy G.; Khosravi, Hassan – British Journal of Educational Technology, 2023
Traditional item analyses such as classical test theory (CTT) use exam-taker responses to assessment items to approximate their difficulty and discrimination. The increased adoption by educational institutions of electronic assessment platforms (EAPs) provides new avenues for assessment analytics by capturing detailed logs of an exam-taker's…
Descriptors: Medical Students, Evaluation, Computer Assisted Testing, Time Factors (Learning)
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Buczak, Philip; Huang, He; Forthmann, Boris; Doebler, Philipp – Journal of Creative Behavior, 2023
Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…
Descriptors: Computer Assisted Testing, Scoring, Automation, Creative Thinking
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Ersen, Rabia Karatoprak; Lee, Won-Chan – Journal of Educational Measurement, 2023
The purpose of this study was to compare calibration and linking methods for placing pretest item parameter estimates on the item pool scale in a 1-3 computerized multistage adaptive testing design in terms of item parameter recovery. Two models were used: embedded-section, in which pretest items were administered within a separate module, and…
Descriptors: Pretesting, Test Items, Computer Assisted Testing, Adaptive Testing
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Yuan, Lu; Huang, Yingshi; Li, Shuhang; Chen, Ping – Journal of Educational Measurement, 2023
Online calibration is a key technology for item calibration in computerized adaptive testing (CAT) and has been widely used in various forms of CAT, including unidimensional CAT, multidimensional CAT (MCAT), CAT with polytomously scored items, and cognitive diagnostic CAT. However, as multidimensional and polytomous assessment data become more…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Test Items
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Gordanier, John; Ozturk, Orgul; Zhan, Crystal – Education Finance and Policy, 2023
Computer-based testing (CBT) is becoming an increasingly popular format of assessment in educational settings. If students face a digital divide in terms of access to computers at school and at home, CBT may exacerbate measured student achievement gaps. In this paper, we use the rollout of CBT in South Carolina starting in 2015 to investigate its…
Descriptors: Computer Assisted Testing, Academic Achievement, Testing Programs, Program Implementation
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Tan, Qingrong; Cai, Yan; Luo, Fen; Tu, Dongbo – Journal of Educational and Behavioral Statistics, 2023
To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item…
Descriptors: Cognitive Tests, Computer Assisted Testing, Adaptive Testing, Accuracy
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Gribbins, Michele; Bonk, Curtis J. – British Journal of Educational Technology, 2023
As universities moved to remotely taught courses during the COVID-19 pandemic, the importance of maintaining academic integrity in online environments intensified. In response, this study explores instructors' perceptions about the role of online proctoring as a tool for their courses with the intent of enhancing the understanding of online…
Descriptors: Teacher Attitudes, Computer Assisted Testing, Supervision, Integrity
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Fink, Aron; Spoden, Christian; Frey, Andreas – Education and Information Technologies, 2023
The replacement of existing technology or the introduction of novel technology into the day-to-day routines of higher education institutions is not a trivial task. Currently, many higher education institutions are faced with the challenge of replacing existing procedures for administering written exams with e-exams. To guide this process, this…
Descriptors: College Faculty, Teacher Attitudes, Intention, Computer Assisted Testing
Jackson, Kayla – ProQuest LLC, 2023
Prior research highlights the benefits of multimode surveys and best practices for item-by-item (IBI) and matrix-type survey items. Some researchers have explored whether mode differences for online and paper surveys persist for these survey item types. However, no studies discuss measurement invariance when both item types and online modes are…
Descriptors: Test Items, Surveys, Error of Measurement, Item Response Theory
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Green, Theresa; Goodridge, Wade H.; Anderson, Jon; Davishahl, Eric; Kane, Daniel – International Education Studies, 2023
The purpose of this study was to examine any differences in test scores between three different online versions of the Mental Cutting Test (MCT). The MCT was developed to quantify a rotational and proportion construct of spatial ability and has been used extensively to assess spatial ability. This test was developed in 1938 as a paper-and-pencil…
Descriptors: Spatial Ability, Measures (Individuals), Computer Assisted Testing, Test Format
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