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Ulrike Padó; Yunus Eryilmaz; Larissa Kirschner – International Journal of Artificial Intelligence in Education, 2024
Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need for high-quality models, which is exacerbated for languages with fewer resources than English; a usability…
Descriptors: Grading, Automation, Test Format, Computer Assisted Testing
Anna Filighera; Sebastian Ochs; Tim Steuer; Thomas Tregel – International Journal of Artificial Intelligence in Education, 2024
Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However,…
Descriptors: Cheating, Grading, Form Classes (Languages), Computer Software
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
Benton, Tom – Research Matters, 2021
Computer adaptive testing is intended to make assessment more reliable by tailoring the difficulty of the questions a student has to answer to their level of ability. Most commonly, this benefit is used to justify the length of tests being shortened whilst retaining the reliability of a longer, non-adaptive test. Improvements due to adaptive…
Descriptors: Risk, Item Response Theory, Computer Assisted Testing, Difficulty Level
Miller, Ronald Mellado; Andrade, Maureen Snow – Research & Practice in Assessment, 2020
Technology use is increasing in higher education, particularly for test administration. In this study, Capaldi's (1994) sequential theory, which postulates that the specific order of reinforcements and nonreinforcements influences persistence in the face of difficulty or failure, was applied to online multiple choice testing situations in regard…
Descriptors: Computer Assisted Testing, Higher Education, Multiple Choice Tests, Test Format
Bahari, Akbar – Open Learning, 2021
This study reports on a review of 286 peer-reviewed articles from 2002-2018 to identify the mainstream assessment tools and strategies adopted for language proficiency assessment in computer-assisted language learning studies. Given the diversity of tools and strategies being adopted for assessment purposes, it was highly critical to trace the…
Descriptors: Language Proficiency, Second Language Learning, Language Tests, Computer Assisted Instruction
Wainer, Howard; And Others – 1990
The initial development of a testlet-based algebra test was previously reported (Wainer and Lewis, 1990). This account provides the details of this excursion into the use of hierarchical testlets and validity-based scoring. A pretest of two 15-item hierarchical testlets was carried out in which examinees' performance on a 4-item subset of each…
Descriptors: Adaptive Testing, Algebra, Comparative Analysis, Computer Assisted Testing