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Bin Tan; Nour Armoush; Elisabetta Mazzullo; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2025
This study reviews existing research on the use of large language models (LLMs) for automatic item generation (AIG). We performed a comprehensive literature search across seven research databases, selected studies based on predefined criteria, and summarized 60 relevant studies that employed LLMs in the AIG process. We identified the most commonly…
Descriptors: Artificial Intelligence, Test Items, Automation, Test Format
Han, Chao – Language Testing, 2022
Over the past decade, testing and assessing spoken-language interpreting has garnered an increasing amount of attention from stakeholders in interpreter education, professional certification, and interpreting research. This is because in these fields assessment results provide a critical evidential basis for high-stakes decisions, such as the…
Descriptors: Translation, Language Tests, Testing, Evaluation Methods
Graf, Edith Aurora – ETS Research Report Series, 2008
Quantitative item models are item structures that may be expressed in terms of mathematical variables and constraints. An item model may be developed as a computer program from which large numbers of items are automatically generated. Item models can be used to produce large numbers of items for use in traditional, large-scale assessments. But…
Descriptors: Test Items, Models, Diagnostic Tests, Statistical Analysis
Embretson, Susan E. – Measurement: Interdisciplinary Research and Perspectives, 2004
The last century was marked by dazzling changes in many areas, such as technology and communications. Predictions into the second century of testing are seemingly difficult in such a context. Yet, looking back to the turn of the last century, Kirkpatrick (1900), in his American Psychological Association presidential address, presented fundamental…
Descriptors: Ability, Testing, Futures (of Society), Psychometrics

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