Transforming Assessment: The Impacts and Implications of Large Language Models and Generative AI
The remarkable strides in artificial intelligence (AI), exemplified by ChatGPT, have unveiled a wealth of opportunities and challenges in assessment. Applying cutting‐edge large language models (LLMs) and generative AI to assessment holds great promise in boosting efficiency, mitigating bias, and fa...
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| Published in | Educational measurement, issues and practice Vol. 43; no. 2; pp. 16 - 29 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Washington
Wiley Subscription Services, Inc
01.06.2024
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| Subjects | |
| Online Access | Get full text |
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| Abstract | The remarkable strides in artificial intelligence (AI), exemplified by ChatGPT, have unveiled a wealth of opportunities and challenges in assessment. Applying cutting‐edge large language models (LLMs) and generative AI to assessment holds great promise in boosting efficiency, mitigating bias, and facilitating customized evaluations. Conversely, these innovations raise significant concerns regarding validity, reliability, transparency, fairness, equity, and test security, necessitating careful thinking when applying them in assessments. In this article, we discuss the impacts and implications of LLMs and generative AI on critical dimensions of assessment with example use cases and call for a community effort to equip assessment professionals with the needed AI literacy to harness the potential effectively. |
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| AbstractList | The remarkable strides in artificial intelligence (AI), exemplified by ChatGPT, have unveiled a wealth of opportunities and challenges in assessment. Applying cutting‐edge large language models (LLMs) and generative AI to assessment holds great promise in boosting efficiency, mitigating bias, and facilitating customized evaluations. Conversely, these innovations raise significant concerns regarding validity, reliability, transparency, fairness, equity, and test security, necessitating careful thinking when applying them in assessments. In this article, we discuss the impacts and implications of LLMs and generative AI on critical dimensions of assessment with example use cases and call for a community effort to equip assessment professionals with the needed AI literacy to harness the potential effectively. |
| Author | Harris, Deborah J. Davier, Matthias Hao, Jiangang Yaneva, Victoria Davier, Alina A. Lottridge, Susan |
| Author_xml | – sequence: 1 givenname: Jiangang orcidid: 0000-0003-0502-7571 surname: Hao fullname: Hao, Jiangang organization: Educational Testing Service – sequence: 2 givenname: Alina A. surname: Davier fullname: Davier, Alina A. organization: Duolingo, Inc – sequence: 3 givenname: Victoria surname: Yaneva fullname: Yaneva, Victoria organization: National Board of Medical Examiners – sequence: 4 givenname: Susan orcidid: 0000-0002-9857-3282 surname: Lottridge fullname: Lottridge, Susan organization: Cambium Assessment, Inc – sequence: 5 givenname: Matthias surname: Davier fullname: Davier, Matthias organization: Boston College – sequence: 6 givenname: Deborah J. surname: Harris fullname: Harris, Deborah J. organization: University of Iowa |
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| Title | Transforming Assessment: The Impacts and Implications of Large Language Models and Generative AI |
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