生成语法
透明度(行为)
衡平法
读写能力
计算机科学
心理学
人工智能
政治学
计算机安全
教育学
法学
作者
Jiangang Hao,Alina von Davier,Victoria Yaneva,Susan Lottridge,Matthias von Davier,Deborah J. Harris
摘要
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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