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Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
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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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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
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Kyung-Mi O. – Language Testing in Asia, 2024
This study examines the efficacy of artificial intelligence (AI) in creating parallel test items compared to human-made ones. Two test forms were developed: one consisting of 20 existing human-made items and another with 20 new items generated with ChatGPT assistance. Expert reviews confirmed the content parallelism of the two test forms.…
Descriptors: Comparative Analysis, Artificial Intelligence, Computer Software, Test Items
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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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Yizhu Gao; Xiaoming Zhai; Min Li; Gyeonggeon Lee; Xiaoxiao Liu – Grantee Submission, 2025
The rapid evolution of generative artificial intelligence (GenAI) is transforming science education by facilitating innovative pedagogical paradigms while raising substantial concerns about scholarly integrity. One particularly pressing issue is the growing risk of student use of GenAI tools to outsource assessment tasks, potentially compromising…
Descriptors: Artificial Intelligence, Computer Software, Science Education, Integrity
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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