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 language | English (US) |
---|---|
Pages | 369-395 |
Number of pages | 27 |
Volume | 54 |
No | 4 |
Specialist publication | Journal of Technical Writing and Communication |
DOIs | |
State | Published - 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