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

Research output: Contribution to specialist publicationArticle

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.

Original languageEnglish (US)
Pages369-395
Number of pages27
Volume54
No4
Specialist publicationJournal of Technical Writing and Communication
DOIs
StatePublished - Oct 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Keywords

  • AI literacy
  • AI-assisted writing
  • ChatGPT
  • feedback loops
  • few-shot
  • prompt engineering
  • prompting techniques
  • rhetorical genre analysis
  • role prompting
  • zero-shot

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