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Yusuf Oc; Hela Hassen – Marketing Education Review, 2025
Driven by technological innovations, continuous digital expansion has transformed fundamentally the landscape of modern higher education, leading to discussions about evaluation techniques. The emergence of generative artificial intelligence raises questions about reliability and academic honesty regarding multiple-choice assessments in online…
Descriptors: Higher Education, Multiple Choice Tests, Computer Assisted Testing, Electronic Learning
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Rebecka Weegar; Peter Idestam-Almquist – International Journal of Artificial Intelligence in Education, 2024
Machine learning methods can be used to reduce the manual workload in exam grading, making it possible for teachers to spend more time on other tasks. However, when it comes to grading exams, fully eliminating manual work is not yet possible even with very accurate automated grading, as any grading mistakes could have significant consequences for…
Descriptors: Grading, Computer Assisted Testing, Introductory Courses, Computer Science Education
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McCaffrey, Daniel F.; Casabianca, Jodi M.; Ricker-Pedley, Kathryn L.; Lawless, René R.; Wendler, Cathy – ETS Research Report Series, 2022
This document describes a set of best practices for developing, implementing, and maintaining the critical process of scoring constructed-response tasks. These practices address both the use of human raters and automated scoring systems as part of the scoring process and cover the scoring of written, spoken, performance, or multimodal responses.…
Descriptors: Best Practices, Scoring, Test Format, Computer Assisted Testing
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Yan Jin; Jason Fan – Language Assessment Quarterly, 2023
In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the…
Descriptors: Language Tests, Artificial Intelligence, Computer Assisted Testing, Test Format
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Botelho, Anthony; Baral, Sami; Erickson, John A.; Benachamardi, Priyanka; Heffernan, Neil T. – Journal of Computer Assisted Learning, 2023
Background: Teachers often rely on the use of open-ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving mathematical problems beyond what is possible through…
Descriptors: Natural Language Processing, Artificial Intelligence, Computer Assisted Testing, Mathematics Tests
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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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Baral, Sami; Botelho, Anthony; Santhanam, Abhishek; Gurung, Ashish; Cheng, Li; Heffernan, Neil – International Educational Data Mining Society, 2023
Teachers often rely on the use of a range of open-ended problems to assess students' understanding of mathematical concepts. Beyond traditional conceptions of student open-ended work, commonly in the form of textual short-answer or essay responses, the use of figures, tables, number lines, graphs, and pictographs are other examples of open-ended…
Descriptors: Mathematics Instruction, Mathematical Concepts, Problem Solving, Test Format
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Jung Youn, Soo – Language Testing, 2023
As access to smartphones and emerging technologies has become ubiquitous in our daily lives and in language learning, technology-mediated social interaction has become common in teaching and assessing L2 speaking. The changing ecology of L2 spoken interaction provides language educators and testers with opportunities for renewed test design and…
Descriptors: Test Construction, Test Validity, Second Language Learning, Telecommunications
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Neha Biju; Nasser Said Gomaa Abdelrasheed; Khilola Bakiyeva; K. D. V. Prasad; Biruk Jember – Language Testing in Asia, 2024
In recent years, language practitioners have paid increasing attention to artificial intelligence (AI)'s role in language programs. This study investigated the impact of AI-assisted language assessment on L2 learners' foreign language anxiety (FLA), attitudes, motivation, and writing skills. The study adopted a sequential exploratory mixed-methods…
Descriptors: Artificial Intelligence, Computer Software, Computer Assisted Testing, Second Language Instruction
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Abdullah Al Fraidan – International Journal of Distance Education Technologies, 2025
This study explores vocabulary assessment practices in Saudi Arabia's hybrid EFL ecosystem, leveraging platforms like Blackboard and Google Forms. The focus is on identifying prevalent test formats and evaluating their alignment with modern pedagogical goals. To classify vocabulary assessment formats in hybridized EFL contexts and recommend the…
Descriptors: Vocabulary Development, English (Second Language), Second Language Learning, Second Language Instruction
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Patrick Kyllonen; Amit Sevak; Teresa Ober; Ikkyu Choi; Jesse Sparks; Daniel Fishtein – ETS Research Report Series, 2024
Assessment refers to a broad array of approaches for measuring or evaluating a person's (or group of persons') skills, behaviors, dispositions, or other attributes. Assessments range from standardized tests used in admissions, employee selection, licensure examinations, and domestic and international large-scale assessments of cognitive and…
Descriptors: Assessment Literacy, Testing, Test Bias, Test Construction