Publication | Open Access
Transforming Assessment: The Impacts and Implications of Large Language Models and Generative AI
56
Citations
46
References
2024
Year
Artificial IntelligenceEngineeringNeeded Ai LiteracyLiteracy EvaluationLarge Language ModelLanguage LearningLanguage ProcessingLanguage Assessment (Second Language Acquisition)Large Language ModelsNatural Language ProcessingTest SecurityComputational LinguisticsLanguage TestingLanguage AcquisitionLanguage Assessment (Speech Language Pathology)Language StudiesAutomated AssessmentMachine TranslationLarge Ai ModelEducational TestingEducational MeasurementAi EducationElectronic AssessmentEducational AssessmentGenerative AiEvaluation TechniqueLinguisticsLanguage Generation
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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