Transforming Assessment: The Impacts and Implications of Large Language Models and Generative AI

Author:

Hao Jiangang1ORCID,von Davier Alina A.2,Yaneva Victoria3,Lottridge Susan4ORCID,von Davier Matthias5,Harris Deborah J.6

Affiliation:

1. Educational Testing Service

2. Duolingo, Inc.

3. National Board of Medical Examiners

4. Cambium Assessment, Inc.

5. Boston College

6. University of Iowa

Abstract

AbstractThe 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.

Publisher

Wiley

Reference118 articles.

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