Improving ChatGPT's Competency in Generating Effective Business Communication Messages: Integrating Rhetorical Genre Analysis into Prompting Techniques

Junhua Wang
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Abstract

This study explores how prompting techniques, especially those integrated with rhetorical analysis results, may improve the effectiveness of artificial intelligence (AI)-generated business communication messages. I conducted an experiment to assess the effectiveness of these prompting techniques in the context of crafting a negative message generated with ChatGPT 3.5 ( n = 85). A multiple regression was calculated to explore prompting techniques’ impact on the negative message grades and how each technique influences the message grade. The results ( F(4, 80) = 31.84, p < .001), with an adjusted R2 = .595, indicate a positive relationship between prompting techniques and the effectiveness of AI-generated messages. This study also identified challenges related to students’ AI literacy. I conclude the study by recommending practical measures on how to incorporate AI into business and professional writing classrooms.
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提高 ChatGPT 生成有效商务交流信息的能力:将修辞体裁分析与提示技巧相结合
本研究探讨了提示技术,尤其是与修辞分析结果相结合的提示技术,可以如何提高人工智能(AI)生成的商业沟通信息的有效性。我进行了一项实验,在使用 ChatGPT 3.5 生成负面信息(n = 85)的情况下,评估这些提示技巧的有效性。我们计算了多元回归,以探讨提示技巧对负面信息等级的影响,以及每种技巧如何影响信息等级。结果 ( F(4, 80) = 31.84, p < .001) 和调整后的 R2 = .595 表明,提示技巧与人工智能生成的信息的有效性之间存在正相关关系。本研究还发现了与学生人工智能素养相关的挑战。最后,我就如何将人工智能融入商业和专业写作课堂提出了一些实用措施。
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