Exploring the potential of using ChatGPT for rhetorical move-step analysis: The impact of prompt refinement, few-shot learning, and fine-tuning

IF 3.1 1区 文学 Q1 EDUCATION & EDUCATIONAL RESEARCH
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引用次数: 0

Abstract

Rhetorical move-step analysis has wielded considerable influence in the fields of English for Academic/Specific Purposes. To explore the potential of using ChatGPT for automated move-step analysis, this study examines the impact of few-shot learning, prompt refinement, and base model fine-tuning on its accuracy in move-step annotation. Our dataset consisted of the introduction sections of 100 research articles in the field of applied linguistics that have been manually annotated for move-steps based on a modified version of Swales’ (1990) Create-a-Research-Space model, with 80 for training, 10 for validation, and 10 for testing. We formulated an initial prompt that instructed the base model to perform move-step annotation, evaluated it in a zero-shot setting on the validation set, and subsequently refined it with greater specificity. We also fine-tuned the base model on the training set. Evaluation results on the test set showed that few-shot learning and prompt refinement both led to significant albeit relatively small performance improvements, while fine-tuning the base model achieved substantially higher accuracies (92.3% for move and 80.2% for step annotation). Our results highlight the potential of using ChatGPT for discourse-level annotation tasks and have useful implications for EAP pedagogy. They also provide key recommendations for employing ChatGPT in research.

探索使用 ChatGPT 进行修辞步骤分析的潜力:及时完善、少量学习和微调的影响
修辞步骤分析在学术/特定用途英语领域具有相当大的影响力。为了探索使用 ChatGPT 进行自动语步分析的潜力,本研究考察了少量学习、提示完善和基础模型微调对其语步标注准确性的影响。我们的数据集由应用语言学领域 100 篇研究文章的引言部分组成,这些文章已根据 Swales(1990 年)的 Create-a-Research-Space 模型的修改版进行了移动步骤人工标注,其中 80 篇用于训练,10 篇用于验证,10 篇用于测试。我们制定了一个指示基本模型执行移动步骤注释的初始提示,并在验证集上对其进行了零次评估,随后对其进行了改进,使其更具针对性。我们还在训练集上对基础模型进行了微调。测试集上的评估结果表明,少量学习和及时改进都带来了显著的性能提升,尽管幅度相对较小,而对基础模型进行微调则大大提高了准确率(移动注释的准确率为 92.3%,步骤注释的准确率为 80.2%)。我们的研究结果凸显了将 ChatGPT 用于话语级注释任务的潜力,并对 EAP 教学法产生了有益的影响。这些结果还为在研究中使用 ChatGPT 提供了重要建议。
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来源期刊
CiteScore
6.60
自引率
13.30%
发文量
81
审稿时长
57 days
期刊介绍: The Journal of English for Academic Purposes provides a forum for the dissemination of information and views which enables practitioners of and researchers in EAP to keep current with developments in their field and to contribute to its continued updating. JEAP publishes articles, book reviews, conference reports, and academic exchanges in the linguistic, sociolinguistic and psycholinguistic description of English as it occurs in the contexts of academic study and scholarly exchange itself.
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