LLMs can Perform Multi-Dimensional Analytic Writing Assessments: A Case Study of L2 Graduate-Level Academic English Writing

• URL: http://arxiv.org/abs/2502.11368v1
• Date: Mon, 17 Feb 2025 02:31:56 GMT
• Title: LLMs can Perform Multi-Dimensional Analytic Writing Assessments: A Case Study of L2 Graduate-Level Academic English Writing
• Authors: Zhengxiang Wang, Veronika Makarova, Zhi Li, Jordan Kodner, Owen Rambow,
• Abstract summary: We use a corpus of literature reviews written by L2 graduate students and assessed by human experts against 9 analytic criteria. To evaluate the quality of feedback comments, we apply a novel feedback comment quality evaluation framework. We find that LLMs can generate reasonably good and generally reliable multi-dimensional analytic assessments.
• Score: 10.239220270988136
• License:
• Abstract: The paper explores the performance of LLMs in the context of multi-dimensional analytic writing assessments, i.e. their ability to provide both scores and comments based on multiple assessment criteria. Using a corpus of literature reviews written by L2 graduate students and assessed by human experts against 9 analytic criteria, we prompt several popular LLMs to perform the same task under various conditions. To evaluate the quality of feedback comments, we apply a novel feedback comment quality evaluation framework. This framework is interpretable, cost-efficient, scalable, and reproducible, compared to existing methods that rely on manual judgments. We find that LLMs can generate reasonably good and generally reliable multi-dimensional analytic assessments. We release our corpus for reproducibility.

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