-
About
Our Story
back- Our Mission
- Our Leadership
- Accessibility
- Careers
- Diversity, Equity, Inclusion
- Learning Science
- Sustainability
Our Solutions
back
-
Community
Community
back- Newsroom
- Discussions
- Webinars on Demand
- Digital Community
- The Institute at Macmillan Learning
- English Community
- Psychology Community
- History Community
- Communication Community
- College Success Community
- Economics Community
- Institutional Solutions Community
- Nutrition Community
- Lab Solutions Community
- STEM Community
- Newsroom
- Macmillan Community
- :
- English Community
- :
- Bits Blog
- :
- Bits on Bots - Continuing the Conversation on Gene...
Bits on Bots - Continuing the Conversation on Generative AI: Prompting and Ethics Frameworks
- Subscribe to RSS Feed
- Mark as New
- Mark as Read
- Bookmark
- Subscribe
- Printer Friendly Page
- Report Inappropriate Content
As educators, we are in the midst, or at least a mis-beginning of a paradigm shift. And, certainly, generative AI (genAI) is becoming a key part of the conversation, offering exciting opportunities but also raising important ethical questions. Recently, the Macmillan Learning community featured my blog post "Bits on Bots: Data-Informed Generative AI Practice: One University’s Journey", which lays a foundation for understanding how institutions like Kennesaw State University (KSU) are navigating this transformative journey.
Today, I want to share the evolution of our AI literacy initiatives at Kennesaw State University and to illustrate how our Rhetorical Prompt Engineering framework has fostered a nuanced understanding of both the ethical and practical dimensions of AI usage among learners and professional writers at varying educational and skill levels.
Our journey began with a central question: How can we empower students to harness genAI effectively while ensuring they remain critically aware of the ethical complexities it introduces? The answer emerged in the form of the Rhetorical Prompt Engineering Method, which was not only inspired by post-process writing practice but also the Markov Chain: a probabilistic model that predicts the next word or sequence in a conversation based only on the current state or previous word(s) without needing the full conversation history, which helps simplify and guide response generation. Initially implemented with both undergraduate and graduate students at KSU, this method prompted learners to engage deeply with their writing processes and AI-generated content. The aim was not only to improve the efficiency of their prompts but also to cultivate a conscientious approach that takes into account broader ethical implications. This approach is unique in treating prompt engineering as a rhetorical writing process—one that’s focused on audience, purpose, style, tone, and contextual awareness.
Building on this foundation, the framework expanded beyond our campus to reach thousands of learners through a module on Coursera, where it continued to evolve and adapt. As a professor and curricular developer in these courses, I have been privileged to observe students from diverse academic and professional backgrounds explore the integration of genAI into their personal and professional contexts. The feedback has been overwhelmingly positive. Learners have consistently reported that the Rhetorical Prompt Engineering Method not only improved the quality of their AI-generated outputs but also heightened their awareness of ethical concerns they may not have previously considered. Hundreds of learners have reported that this method assists them in developing clarity and specificity in their prompting and increased accuracy and usefulness of their outputs. This method is now a core part of graduate-level courses, including Prompt Engineering for Writers, grant-writing, Introduction to Professional Writing, and the proposed Graduate Certificate in AI Writing Technologies in our English Department's graduate curriculum.
The implementation and iterative refinement of this framework have yielded demonstrable improvements in the quality of student outputs. Whether by clarifying the purpose, adjusting audience, tone, or ensuring that generated prompts avoid harmful biases, this method has had a measurable impact for learners training to be, or who are already, professional writers. Thousands of learners, both at KSU and across Coursera, have applied this approach to generate outputs that are more effective, ethical, and precise.
To further support this process, we have developed a visual tool known as the Ethical Wheel of Prompting. This tool encourages learners to reflect on four essential criteria: Usefulness, Relevance, Accuracy, and Harmlessness. Each time a prompt is crafted or an output is edited, learners are urged to consider these criteria as a means of ensuring not only effectiveness but also responsibility in genAI use. We have had positive small-scale student response and continue to refine this method as we move forward with piloting.
Below, I have included both the Rhetorical Prompt Engineering Method and the Ethical Wheel of Prompting. These visuals are intended to illuminate the process and demonstrate the practical application of human-genAI interactions. Whether you are composing a blog post, editing a professional communication, or generating content ideas, these steps can significantly enhance the quality and integrity of the work produced.
Generative AI is a transformative tool, and with thoughtful, ethical engagement, it can serve as a catalyst for meaningful and impactful communication. I invite you to connect with me on LinkedIn or via email to continue exploring and expanding our understanding of both the affordances and limitations of these emerging technologies.
Jeanne Beatrix Law is a Professor of English and Director of Composition at Kennesaw State University, focusing on generative AI (genAI) and digital civil rights histography. Her AI literacy work has global reach, including multiple presentations of her Rhetorical Prompt Engineering Framework at conferences like Open Educa Berlin and the Suny Council on Writing. She has led workshops on ethical genAI for diverse institutions and disciplines at Eastern Michigan, Kent State, and CUNY’s Ai Subgroup. She and her students have authored publications on student perceptions of AI in professional writing. Jeanne also co-authored The Writer's Loop: A Guide to College Writing and contributed to the Instructor's Guide for Andrea Lunsford's Everyday Writer. She has authored eight Coursera courses on genAI and advocates for ethical AI integration in educational spaces in both secondary and higher education spaces as a faculty mentor for the AAC&U’s AI Pedagogy Institute.
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.