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Potentiels des grands modèles de langage pré-entraînés pour améliorer l'efficacité de l'éducation

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  • Kim, Donghyun

Abstract

L'application de modèles de langage pré-entraînés (PLM) dans le traitement du langage naturel (TAL) a été largement reconnue pour ses performances exceptionnelles dans diverses tâches de TAL et dans des benchmarks publics. L'intégration des PLM dans l'éducation a la possibilité de transformer la façon dont l'apprentissage et l'enseignement sont menés. Cependant, il est crucial de peser à la fois les avantages et les inconvénients qui peuvent accompagner une telle intégration. Pour tirer pleinement parti des PLM et minimiser les impacts négatifs, une approche prudente et responsable est nécessaire lors de l'intégration des PLM dans l'éducation. Ce document se penche sur les avantages et les inconvénients de l'utilisation des PLM dans l'éducation et offre des conseils pour les progrès futurs.

Suggested Citation

  • Kim, Donghyun, 2023. "Potentiels des grands modèles de langage pré-entraînés pour améliorer l'efficacité de l'éducation," OSF Preprints fqh83_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:fqh83_v1
    DOI: 10.31219/osf.io/fqh83_v1
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