April 30, 2024, 4:50 a.m. | Stefano Bann\`o, Hari Krishna Vydana, Kate M. Knill, Mark J. F. Gales

cs.CL updates on arXiv.org arxiv.org

arXiv:2404.18557v1 Announce Type: new
Abstract: Automated essay scoring (AES) to evaluate second language (L2) proficiency has been a firmly established technology used in educational contexts for decades. Although holistic scoring has seen advancements in AES that match or even exceed human performance, analytic scoring still encounters issues as it inherits flaws and shortcomings from the human scoring process. The recent introduction of large language models presents new opportunities for automating the evaluation of specific aspects of L2 writing proficiency. In …

abstract aes arxiv assessment automated cs.cl educational essay flaws gpt gpt-4 human human performance language match performance scoring technology type

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